E-COMMERCE AND SEMANTIC WEB

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Oct 22, 2013 (3 years and 5 months ago)

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E
-
Commerce and Semantic Web

Antonis Misargopoulos, Athina Tziaki



1

UNIVERSITY OF CRETE

COMPUTER SCIENCE DEP
ARTMENT





CS
-
566

WEB SEMANTICS






PHASE 4


E
-
COMMERCE AND SEMANTI
C WEB







ATHINA TZIAKI (MET)

ANTONIS MISARGOPOULO
S (MET)





JUNE
, 2003

HERAKLION, CRETE



E
-
Commerce and Semantic Web

Antonis Misargopoulos, Athina Tziaki



2


ABSTRACT


The Semantic Web will bring structure to
the content of Web
pages,

being an extension of the current Web, in which
information is given a well
-
defined

meaning. Especially
within e
-
commerce applications, Semantic Web technologies

in the form of ontologies and metadata are becoming
increasingly pre
valent

and important. In this work, we
present a semantic e
-
commerce lifecycle and describe core
issues like data integration and agent use. Finally, there are
some existing semantic e
-
commerce applications and their
descriptions.






































E
-
Commerce and Semantic Web

Antonis Misargopoulos, Athina Tziaki



3


TABLE OF CONTENTS



1.

Introduction

................................
................................
.............................

4

2.

Semantic Web

................................
................................
........................

4

3.

Ont
ologies

................................
................................
...............................

5

4.

Semantic Web Support for the B2B e
-
Commerce Lifecycle

....................

7

4.1.

Lifecycle Stages

................................
................................
...............

7

4.2.

Matchmaking

................................
................................
....................

8

4.3.

Negotiation

................................
................................
.......................

9

4.4.

Description Language for B2B E
-
Commerce Lifecycle

...................

11

4.4.1.

Requirements

................................
................................
.......

11

4.4.2.

Why DAML+OIL is a good solution?

................................
.....

12

4.4.3.

Modelling
using DAML+OIL

................................
..................

12

4.4.4.

Operations over Descriptions

................................
................

17

4.4.5.

Implementation

................................
................................
.....

18

5.

Next Generation e
-
Commerce

................................
..............................

19

6.

Integration

................................
................................
.............................

20

6.1.

Unified Catalog

................................
................................
...............

23

6.2.

Mapping Rules

................................
................................
................

24

7.

Economic Impact of Evolving Semantic Web

................................
........

26

7.1.

E
-
Commerce at Present

................................
................................
.

26

7.2.

Semantic E
-
Commerce
................................
................................
...

27

8.

Existing Applications and Frameworks

................................
.................

28

8.1.

KAON

................................
................................
.............................

28

8.1.1.

Requirements

................................
................................
.......

28

8.1.2.

Conceptual Architecture

................................
.......................

29

8.2.

MOMIS

................................
................................
...........................

31

8.3.

SemanticEdge

................................
................................
................

33

9.

Conclusion

................................
................................
............................

35

10.

Related Papers

................................
................................
.....................

36

11.

References

................................
................................
...........................

37
















E
-
Commerce and Semantic Web

Antonis Misargopoulos, Athina Tziaki



4

1.

Introduction


The competitiveness of companies active in areas with a high rate of change
depends heavily on how effectively they acquire, m
aintain, exchange and
access their knowledge, and whether they can deliver the right information to
the right individual customer or business at the right time. Due to globalization
and the impact of the Internet, many organizations are increasingly
geogra
phically dispersed and organized around virtual teams. Such
organizations need knowledge management and organizational memory tools
that encourage users to understand each other’s changing contextual
knowledge and foster collaboration while capturing, repr
esenting and
interpreting the knowledge resources of their organizations.


At the same time, competitiveness of companies

will also depend on
the products and mainly the services they offer. The growth of a wide range of
e
-
commerce services, both to indivi
duals and between businesses, is
contributing to the increasing international trading of products and services.
The ability to find, interrogate and exchange knowledge is fundamental for
Business
-
to
-
Business (B2B)

and
Business
-
to
-
Customer (B2C)

e
-
Commerce.



The Web in its’ current form is an impressive success with a growing
number of users and information sources.
Tim Berners
-
Lee
, the inventor of
the

WWW, coined the vision of a Semantic Web in which background
knowledge on the meaning of Web resources is
stored through the use of
machine
-
processable (meta
-
)

data. The SemanticWeb brings structure to the
content of Web pages, being an extension of the current Web, in which
information is given a well
-
defined meaning. Thus, the SemanticWeb will be
able to sup
port automated, electronic services using semantics
-
based
descriptions. These descriptions are seen as a key factor to finding a way out
of the growing problems of traversing an ever expanding Web. In this sense,
ontologies and metadata are becoming increa
singly prevalent and important
in a wide range of e
-
commerce applications.


The technical foundation of the SemanticWeb is RDF (Resource
Description Framework) which provides a generic core data model. Several
software components, such

as parsers, schema a
nd metadata editors,
repositories, have already been developed. However, they generally fail to
meet the requirements for sophisticated e
-
Commerce projects. To support
advanced applications much more specialized, comprehensive and
inte
g
r
ated
tools are requ
ired.




2.

Semantic Web


The term
“Semantic Web”

encompasses efforts to build a new WWW

architecture that

enhances content with formal semantics. This will enable
automated agents to reason

about

Web content, and carry out more
intelligent tasks on behalf of

the user. ”Expressing

meaning” is the main task
E
-
Commerce and Semantic Web

Antonis Misargopoulos, Athina Tziaki



5

of the Semantic Web. Tim Berners
-
Lee has conceived
a five
-
layer
architecture for the Semantic Web which is presented
as follows:

i.

XML
-

The syntax layer
:

XML allows to markup arbitrary content by
means of nes
ted,

attributed elements. The names of these elements don’t
say anything about what the

structure means, therefore further means are
required for the Semantic Web and the

role of XML is reduced to a syntax
carrier.


ii.

RDF
-

The data layer
:

RDF allows the enc
oding, exchange and reuse of
structured

metadata. Principally, information is represented by very
generic means, i.e. directed

partially
labelled

pseudographs. This graph
may be serialized using XML. Contrary

to XML, RDF allows
assigning

global identifiers

to resources and allows
referring and extending

statements made in other documents. This feature is the main motivation
for its

use as
a

data layer.


iii.

The ontology layer
:

The third basic
component of the Semantic Web
comprises

ontologies.

Ontologies descri
be formal, shared
conceptualizations of a particular domain of interest. This description can
be used to describe structurally heterogeneous and distributed

information
sources such as found on the Web.

By defining shared and common
domain theories and voc
abularies, ontologies help

both people and
machines to communicate concisely, supporting the exchange of
semantics

and not only syntax.

The basic building
block for ontologies is

concepts, which are typically hierarchically

organized in a concept
hierarchy
. These concepts can have properties which establish

named
relations to other concepts. Several representation languages have been

proposed for the specification of ontologies.

Ontologies are presented in
section 3 with more details.


iv.

The logic layer
:

The
logic layer consists of rules that enable inferences,
e.g. to choose

courses of action and answer questions.



v.

The proof layer
:

A proof layer has been conceived to allow the
explanation of given

answers generated by automated agents.
Naturally,
we

might wa
nt to check the results

deduced by an

agent, this will require
the translation of its internal reasoning

mechanisms into some unifying
proof representation language.



3.

Ontologies


Ontologies
, that provide shared and common domain theories, will be a key
fo
r such a Semantic Web. They can be seen as metadata that explicitly
represent semantics of data in machine
-
processable way. Ontology
-
based
reasoning services for providing various services. Ontologies help people and
computers to access the information the
y need, and effectively communicate
with each other. Therefore they have a crucial role to play in enabling content
-
based access, interoperability, and communication across the Web, providing
E
-
Commerce and Semantic Web

Antonis Misargopoulos, Athina Tziaki



6

it with a qualitatively new level of service. Semantic Web weave
s together a
net, linking incredible large part of the human knowledge and complements it
with machine processability.



It is clear that if an e
-
services approach to e
-
commerce is to become
widespread, standarisation of
o
ntologies, message content and me
ssage
protocols will be necessary.
The popularity and press surrounding the
release of XML has created great interest in
standards
within particular
communities (organizations) that focus on representing and manipulating
content. The dream is that these s
tandards will enable consumers and B2B
systems to mere accurately search information on the Web within these
communities. The expansiveness and diversity of the Web creates a need for
small set standards semantic primitives that have the same meaning and
i
nterpretation across communities. Such a standard set of primitives should
take into account existing efforts in ontology, and in e
-
commerce contents
standards.



The good news is that most of the
existing
workshop
s seem

to have
taken for granted that onto
logy is required for having web semantics.
However
they have mostly

focused on the
form

rather than the
content

of
these ontologies.


Nicola Guarino

defines
ontology

to be an implemented artifact that
attempts to constrain the intended meaning of a vocabu
lary by eliminated
unintended models
in the interpretation.
Differentiating them only in terms of
their
ontological depth
, we present spectrum of ontology kinds as follows:

i.

Lexicon (Vocabulary with NL definitions)

ii.

Simple Taxonomy

iii.

Thesaurus (Taxonomy plus
related terms)

iv.

Relational model (Unconstrained use of arbitrary relations)

v.

Taxonomy and relational models (Type restrictions and isA links, some
notion of inheritance)

vi.

Fully Axiomatized theory


Libraries, for instance, have had three interesting ontologies

for a long time
(
Welty

and
Jenkins
, 1999), though all of these are quite fundamentally
affected by digitization and the web:

i.

The
card
-
catalog
ontology, which has come to define metadata
(author, title, publisher).

ii.

The
bibliographic

ontology, which define
s records for articles inside
periodicals and other documents.

iii.

The
subject

ontology, which carves the world into di
s
crete subject
areas.


As a result of the huge surrounding XML and in order to support e
-
commerce
efficiently, other ontology efforts have be
en ongoing for some time:

i.

General

contents standards and ontologies (WordNet, CYC, ISO/BSR,
CALS/UDEF)

ii.

Process

standards (NIST/PSL ontology, DARPA/CPR)

iii.

Product

standards (ISO/STEP, UN/SPSC, RosettaNet)

iv.

Information

media standards (Dublin Core, INDECS, CIDO
C)

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-
Commerce and Semantic Web

Antonis Misargopoulos, Athina Tziaki



7

v.

Conceptual

modelling and
representation

standards (UML meta
-
model,
EPISTLE).



4.

Semantic Web Support for the B2B e
-
Commerce
Lifecycle


In this section, we are going to present a lifecycle of a Business
-
to
-
Business
e
-
commerce interaction, and show how th
e Semantic Web can support a
service description language that can be used throughout this lifecycle. By
using DAML+OIL, a service description language sufficiently expressive and
flexible has been developed to be used not only in
advertisements
, but also
in
matchmaking

queries,
negotiation

proposals and
agreements
. We also
identify which operations must be carried out on this description language if
the B2B lifecycle is to be fully supported. We do not propose specific standard
protocols, but instead argue

that these operators are able to support a wide
variety of interaction protocols, and so will be fundamental irrespective of
which protocols are finally adopted.


4.1.

Lifecycle Stages



The lifecycle model, we present, helps us understand the interactions
wh
ich take place between businesses engaged in e
-
commerce. This model
follows the lifecycle of an interaction between two (or more) parties and has
the following stages:

i.

Matchmaking
: A trader locates other traders that it could potentially do
business with.
This is done by some traders placing
advertisements
,
and others making queries over these advertisements.

ii.

Negotiation
: The trader enters into negotiation with one or more of
these potential business partners, to see if they can agree mutually
acceptable te
rms of business. This is done through an interchange of
negotiation proposals

describing constraints on an acceptable deal.
The outcome of this is an
agreement
, specifying the terms that both
parties consider acceptable. These terms could include a definit
ion of
the good or service being traded, prices, delivery date, etc.

iii.

Contract Formation
: The agreement is transformed into a legally
binding
contract.

iv.

Contract Fulfilment
: The parties carry out the agreed transaction,
within the parameters specified in th
e contract. The transaction may be
automatically monitored, and parties would be warned if any behaviour
outside the agreed terms of the contract takes place.



In order to make this framework efficient and automated, interactions
throughout this lifecycl
e must be standardised by the industries using it.
Standarisation must take place at three levels:


E
-
Commerce and Semantic Web

Antonis Misargopoulos, Athina Tziaki



8

i.

Standards for business
-
specific ontologies which describe goods,
services and contracts being traded. These ensure that when one
trader uses a set of terms
to describe a given good, another trader will
be able to interpret then accurately.

ii.

Standards for specifying the format of advertisements, proposals,
contracts and other constructs which are used during B2B interactions.
These standards would specify the s
yntax of these constructs, with the
semantics being defined by the ontologies. Hence, these standards
need not be business
-
specific.

iii.

Standards that specify the protocols which traders use to interact with
each other during different phases of the B2B lifec
ycle. These
determine the messages that are sent back and forth containing the
standards constructs described above.



The ARPA knowledge
-
sharing project was the first to tackle these
standardisation issues. Ontolingua provides a tool for defining standa
rd
ontologies, KIF a language for representing information and KQML a set of
messages for exchanging this information. The FIPA agent standardisation
effort has defined a messaging language, and protocols for conducting B2B
interchanges such as auctions. W
hile some of the ideas developed in these
efforts are clearly important (such as the notion of advertising and facilitators),
they do not provide appropriate primitives for defining the constructs used in
e
-
commerce.



In the following sections we focus on

the first two stages of the e
-
commerce lifecycle above: Matchmaking and Negotiation. In addition, we
describe different interaction protocols that can be used.


4.2.

Matchmaking

Matchmaking is the process whereby potential trading partners become
aware of each

other’s existence. A buyer wishing to purchase access to a
service must locate potential service providers able to meet its needs. The
buyer’s requirements may initially be not fully specified, and the service
providers may be able to offer a range of ser
vices. The process of
matchmaking should not result in the service becoming fully specified: this is
the purpose of the negotiation phase which follows. Instead, the matchmaking
phase should result in a buyer (or service provider) having a list of potentia
l
trade partners, each with an associated partially specified service description.
This description defines the set of
possible services

the provider can offer
which are of interest to the buyer. Using the notion of agents, we present a list
of canonical e
xamples using different protocol to accomplish this.

1.

A buyer broadcasts its requirements to all agents in the system,
irrespective of their abilities. Those agents able to meet the buyer’s
need reply with information about what they are able to offer. This

protocol is used at the start of
Contract Net negotiation
protocol [1].


2.

Whenever a service provider joins the agent community, or alters its
capabilities, it broadcasts a specification of the service it offers to all
E
-
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Antonis Misargopoulos, Athina Tziaki



9

agents. When an agent wishes to use a

service, it contacts just those
agents able to meet its needs.


3.

An agent community has a centralised facilitator agent, which provides
a yellow
-
pages service. Service providers send advertisements,
consisting of descriptions of the service they offer, to
the facilitator.
Buyers send queries, and receive lists of providers potentially able to
satisfy their requirements in response. UDDI [2] provides simple
example of such a service. There are several variants on this protocol:
buyers may be able to submit p
ersistent queries, allowing them to be
informed of new descriptions as they arrive. Buyers may be permitted
to advertise alongside or instead of providers, and providers may be
permitted to make queries.


4.

An agent community may have several facilitator age
nts, each
specialising in information about a given class of service. A buyer can
either contact the appropriate facilitator, if they know which, or contact
a single “meta
-
facilitator”, which will direct their query appropriately.



Despite these different

agent architectures and communication
protocols that can be used to achieve the matchmaking process, we can
identify clear
roles

which are common to all of them. We have a
repository

of
information about services or service requirements, which is maintain
ed by
the
repository host
. Agents adopting
advertiser

role are willing to
advertise

descriptions of services in the repository. These are usually, though not
always, service providers. They may be buyers, advertising a service request,
or may be marketplac
es offering environments where such services can be
traded. Similarly, agents adopting the
seeker

role wish to locate appropriate
advertisers. Seekers can
query

a repository, via the repository host, and may
be able to
browse

the repository.


As it is obvi
ous, different protocols may be appropriate in different
situations, depending on the expected message flow. Hence, it is not
appropriate to standardise on a unique protocol for all agent systems.
Instead, we should allow choice from a variety of such prot
ocols, but
standardise aspects of the roles which are common to all of them. Protocol
specifications determine where information is stored, and how appropriate
messages are passed to access it. Role specifications determine how the
information is represent
ed, accessed and used.


4.3.

Negotiation

The
negotiation
stage of the e
-
commerce interaction lifecycle refines the
abstract service specification from the matchmaking phase to a concrete
agreement

between two parties. Negotiation can be one
-
to
-
one, one
-
to
-
many

or many
-
to
-
many, and as a result, many different protocols have been
designed to carry this out. Negotiation protocols determine the interchange of
messages which take place during the negotiation, and the roles by which the
negotiation must abide.


On
e
-
to
-
one protocols include the shop
-
front, where a seller simply
offers a good at a fixed price, and iterated bargaining, with buyer and seller
E
-
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Antonis Misargopoulos, Athina Tziaki



10

taking turns to exchange proposed agreements. One
-
to
-
many protocols
include the English auction [3], the Dutch a
uction and the Contract Net.
Finally, many
-
to
-
many protocols include the Continuous Double auction and
the Call auction.



In the same way, we analysed the different protocols for matchmaking
in the previous section, we can analyse the different negotia
tion protocols and
identify roles and behaviours common at all. Hence, in each case there are at
least two
negotiation participants
trying to make a deal with each other. In
addition, there is at least one (possible more)
negotiation host
, responsible for
enforcing the rules of the negotiation and ensuring it goes smoothly. Before
negotiation can begin, the parties have already agreed roughly what the
negotiation is about (usually as a result of the matchmaking process). So, this
places a restriction on the

parameters and values to be negotiated, which is
called
negotiation template.

The negotiation template refers to a common
ontology accepted by all participants in the negotiation. It defines a schema
for valid
negotiation proposals

that participants submi
t to each other. The
schema declares which fields are admissible and how their values are
constrained. A proposal is a further refinement of the negotiation space that
represents a configuration of parameters that would be acceptable to the
submitter. The
result of the negotiation process is an
agreement
.


That is a configuration of parameters that is non
-
ambiguous and can
be used during the execution phase to instantiate the service. Therefore we
can define the negotiation process as the process through w
hich participants
move from a pre
-
agreed negotiation template to an agreement, via an
exchange of negotiation proposals. A single negotiation may involve many
parties, resulting in several agreements between different parties and some
parties who do not re
ach agreement. For example, a stock exchange can be
viewed as a negotiation where many buyers and many sellers meet to
negotiate the price of a given stock. Many agreements are formed between
buyers and sellers, and some buyers and sellers fail to trade.



The three main
actions/operations

which the negotiation host carries
out during the abstract negotiation process as presented earlier are
summarized as follows:

1.

Validation: When participants submit proposals, they first need to be
validated with respect
to the negotiation template. The validation step
consists in making sure that the proposal is a more constrained form of
the agreement template. That is, the constraints over the parameters in
the proposal must be tighter that the corresponding ones in the

agreement template. The constraints represent acceptable values to
the proposing participant.

2.

Protocol Checking: The proposal must be submitted according to the
rules of the protocol which governs the way the negotiation takes
place. These rules specify (
among other things) who can make
proposals, when they can be made, and what proposals can be
submitted in relation to previous submissions. For example, auctions
often have a ‘bid improvement’ rule that requires any new proposal to
buy to be for higher pri
ce than the previous proposals.

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11

3.

Agreement Formation; If an agreement is to be made, there must be at
least two valid proposals which are compatible with each other.
Proposals are compatible if there is an identical fully
-
instantiated form
of each.



In the

following section, we declare a language to be sufficiently
general and flexible to cover the matchmaking phase.


4.4.

Description Language for B2B E
-
Commerce Lifecycle

If the constructs and operations, declared above, are to be standardized, we
wish to build
the constructs from a declarative language for describing
services. In addition, we need to show that this language can support the
required operations over it. In the following sections, we present the
necessary requirements and show how DAML+OIL satisfy
most of them.


4.4.1.

Requirements

A description language for B2B e
-
commerce lifecycle should satisfy the
following requirements:


i.

Description should offer a high degree of flexibility and expressiveness.
Parties must have total freedom to create the service desc
ription.
Different advertisers will want to describe their services with different
degrees of complexity and completeness, and our language must be
adaptable to these needs. Similarly, a negotiation proposal may be
very descriptive in some aspects, but lea
ve others less specified and
open for further negotiation. Therefore, the ability to express
semi
-
structured

data is required.


ii.

Descriptions need to share a common semantics. Moreover
descriptions should be able to use vocabularies created by different
sta
ndard bodies or industry sectors. Therefore support for
interoperable ontologies is needed.


iii.

Descriptions should easily lend themselves to performing the
operations described in the negotiation and matchmaking sections. In
particular, matching of advertise
ments with queries during
matchmaking, validation of negotiation proposals against the
negotiation template, and compatibility checking of two negotiation
proposals to determine if an agreement can be made.


iv.

Descriptions should express restrictions and con
straints. Whether it is
an offer or a request, it is often the case that what is expressed is not a
single instance of a service but rather a conceptual definition of the
acceptable instances. A natural way of describing this is by expressing
constraints o
ver the parameters of the service.



E
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Antonis Misargopoulos, Athina Tziaki



12

4.4.2.

Why DAML+OIL is a good solution?

DAML is a DARPA program aiming to provide a language and tools for the
semantic web. One the most promising technologies it has produced so far is
the DAML+OIL ontology language. DAML+OI
L will serve as starting point for
the design of the future Web Ontology Language from W3C.



DAML+OIL is a good candidate for the language we are looking for,
and meets the requirements introduced in section above:


i.

It provides a reasonable level of flex
ibility and extensiveness while
keeping a nice balance between expressiveness and decidability. It
offers support for types, which greatly enhances the expressiveness
and modularity of the descriptions.


ii.

DAML+OIL offers support for ontologies. It is almos
t integrated with
tools such as OilEd [4] and Protégé [5] which make the generation of
new ontologies for service descriptions much easier. Both tools are
being worked on to support the full DAML+OIL specification.


iii.

DAML+OIL is a good candidate for express
ing descriptions that will be
subject to the operations of matching, proposal validation and
agreement formation. As we will present in the following sections, all
the operations can be expressed in terms of the subsumption
operation. DAML+OIL descriptions

lend themselves very well to this
operation and mature tools exist that can perform this on DAML+OIL
descriptions.


iv.

DAML+OIL offers some support for expressing constraints, while still
maintaining decidability. Description logics constructors allow
restri
ctions on objects, and XML schema allows unary constraints on
datatypes. It is worth noting that DAML+OIL does not support n
-
ary
datatype constraints, which may be a problem for real e
-
commerce
applications (i.e. the shipping cost is waved when the sum of

the length
and width of the product is below a certain threshold).



Furthermore, because DAML+OIL is expressed in RDF and XML
schema, it provides the added advantage that many resources and toolsets
developed for these technologies can be applied to the

B2B interaction
lifecycle. In the next section, we explain how DAML+OIL can be used to
describe the various descriptions that are used in the e
-
commerce lifecycle.


4.4.3.


Modelling using DAML+OIL

Service descriptions ontologies and domain specific ontologies w
ill have an
important role to play in order to achieve the semantic level of agreement
between the various parties. For the sole purpose of the following examples,
we define a simple service description ontology along with an ontology for the
sale and deli
ver of computers. To keep the descriptions concise, we use the
description logics notation which is equivalent to the RDF DAML+OIL syntax.

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13

The description ontology:

We use the
Description

class as a common
superclass for

Advertisement, Query, Template
and

Proposal.

An agreement
is an instance of a particular negotiation template.





The service ontology:

Two services are defined in this ontology:
Sales

and

Delivery.

A Sale describes the sale of one Product through the object
property, for a unit price and

quantity given by the respective datatype
properties.





We use the
CompositeService

class and the
isComposedOf

property
to leave a choice to model composite services. When using the
isComposedOf property to specify component services, the component
se
rvice can only match if the main service also matches. Alternatively, a
composite service can be modelled as a boolean combination of component
services. In this case, any single component service can match. For instance,
if we consider a service of sale a
nd delivery of a computer, we can model it
as a service of sale of computer which contains delivery as a sub
-
service or
as the conjunction of both base services. In the first case, the service is
considered as being primarily a service of sale, and would n
ot be matched
with delivery services whereas in the second case it would. In addition, we
have chosen to model the service of Sale to include the buyer and seller roles
as properties. In doing so, we allow the buyer to specify who they are and
who they wou
ld like to do business with.



The PC ontology:

The
PC

class is a subclass of
Product

and must have at
most one
Processor

and one amount of
memory
.

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The Participant ontology:

Public information about prospective advertisers
and negotiators is organized in an ontology, following the yellow pages
model. The ontology is built from information that individuals and/
or
companies are requested to provide at registration time. Such information is
then used at matchmaking and negotiation time to verify compatibility of
advertisements and proposals. For instance a buyer requiring service
provision from an ISO9001 certifie
d company will only be matched with
advertiser that declare to have ISO9001 certification. For the purpose of the
examples, we define some disjoint classes
R1
,
R2
, and
R3

that will represent
participant identities.



Now we are going to give an example fo
r each description type, using
the ontologies just defined:





Advertisement

An advertisement is expressed as a DAML+OIL class defined as the boolean
combination of a set of restrictions over abstract properties and datatype
properties. In Description Logic
s terms, advertisements are expressed as T
-
Boxes.

The following example shows an advertisement where
R1

would like to buy
some PCs. More precisely,
R1

is advertising for the
Sale

and
Delivery

service.
The restrictions over the
Sale

concept are that:

i.

items
must be PCs with at least 128 Mb of memory;

ii.

quantity of PCs being bought will be less than 200;

iii.

unit price must be less than 700.

Since the advertiser is not interested in getting results of delivery services
only, they chose not to describe their adver
tisement as being a
Sale

service
and a
Delivery

service (i.e. by subclassing the intersection of
Sale

and
Delivery
), but rather as being a
Sale

service that
has

a
Delivery

service.

The restrictions on the
Delivery

service are the following:

i.

goods must be d
elivered before the 15/12/2001;

ii.

goods must be delivered in Bristol.

In description logics notation, this advertisement can be written as:

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As we can see from the ontology of the
Sale

service, we require both
the
buyer

and the
seller

roles to be part of the information that is specified in
the agreement. When submitting an advertisement, an advertiser who wan
ts
to play the role of a seller (resp. a buyer) should restrict the
seller

(resp.
buyer
) property to be its identifier. As the ontology shows, it is not forced to do
so, but it is in its best interest. If it does not, it would be matched with
advertisement
s of other sellers (resp. buyers). The seller (resp. buyer) can
leave the
buyer

(resp.
seller
) property unconstrained, or can constrain it to be
a certain subset or subcategory if they want to focus business on a certain
set, for example, a pre
-
qualified s
et of trusted buyers.
Advert2

above is made
by seller
R1
who wishes to avoid doing business with buyer
R3
.





Query

A Query is similar to an Advertisement. It is also a T
-
Box. We give an
example of a Query where the seeker is looking for all buyers and sell
ers of
PCs with an Athlon processor and who are also requesting or providing
delivery.






Negotiation Templat
e

After matchmaking, some parties can choose to enter into negotiation to
determine the exact terms of service delivery. The negotiation template
represents what is in common between all parties and is the starting point for
negotiation. It also serves as
a guide to scope the negotiation: negotiation
proposals must comply with this template. In DAML+OIL terms, they would
have to be subclass of this template.

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Negotiation Proposal

As stated above, a negotiation proposal must be a subclass of the negotiation
template associated with the ongoing negotiation. We now give an example of
negotiation proposal which satis
fies the template
Template1
:





Agreement

When a negotiation terminates with an agreement acceptable to both
parties,
this agreement must specify the service that is going to be exchanged in an
exact and non
-
ambiguous manner. Hence, whereas a negotiation proposal is
a T
-
box, an agreement must be a fully
-
instantiated instance of the negotiation
template. For this
reason, we model an agreement as an A
-
Box.


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In figure

above, we give an example in RDF syntax of an Agreemen
t reached
in a negotiation with
Template1

as its negotiation template.

4.4.4.

Operations over Descriptions

In this section, we present specifications of the operations we presented in
previous sections, together with examples of their operation, and identify the
core functionality required by a
reasoner

to execute them.





Matchmaking:


Let

be the set of all advertisem
ents in a given advertisement repository. For
a given query or advertisement,
Q
, the matchmaking algorithm of the
repository host returns the set of all advertisements which are compatible,



A set of descriptions a
re compatible if their intersection is satisfiable:




For example, consider the following advertisement:




The intersection of this advertisement with
Advert1

above is satisfiable, as
AgreementBetweenR1andR2

is an

instance of both advertisements.
Hence,






Validation:


As we have seen previously, the negotiation host, o
n receiving a proposal
,
must initially check that it is valid. It is valid if it is a more constrained versi
on
of the negotiation template

for this negotiation. In description logic, this
means that the negotiation
host must check that

subsumes
. Formally,
this can be specified as:





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Agreement Formation:


Agreement formation requires the negotiation host to identify all pairs of
proposals which are compatible. Protocol specific rules are then used to
determine exactly which of these pairs are used to form an agreement, and
how exa
ctly to generate the final agreement. Compatibility can be determined
using the compatibility operator defined for matchmaking. Hence, the first
stage of agreement formation can be specified as follows:


Let
be the set of all valid proposals currently registered with the negotiation
host.






Note that only two atomic operations are required to define the
operations specified above:




獡瑩tf楡i楬楴i




獵b獵mp瑩on





A standa
rd description logics reasoner is able to carry out both of
these. Satisfiability lies at the core of such a reasoner, as all other reasoning
or inference techniques are transformed into satisfiability checks. The
subsumption operator is already defined by

the DAML+OIL
subClassOf
,
because our service descriptions are expressed as DAML+OIL classes (i.e.
description logics concepts). A description logics reasoner can check whether
two concepts subsume each other. Hence, a description logics reasoner
provides
a good platform to implement the operations required in the B2B e
-
commerce interaction lifecycle.


4.4.5.


Implementation

According to the specification declared above, a prototype matchmaking
system has been implemented based on the FaCT [6] reasoner, operating
on
services descriptions in DAML+OIL. A full description of the prototype can be
found in [7].


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5.

Next Generation e
-
Commerce


Many consumers do not trust the Internet to provide robust security for online
transactions, and many businesses neither trust e
-
c
ommerce systems nor
believe they will be able to evaluate or control their business risk when using
them. In addition to the trust problem, the lack of automation is another major
problem in present e
-
commerce. Currently, almost all companies offer, or
pla
n to offer, products for purchase over the Internet using e
-
commerce.
However, none of their e
-
commerce sites is truly automated: human
intervention is required for browsing, selecting, ordering and paying for
products. In other words, current e
-
commerce s
ites do not include semantic
representations of data, services, processes, or business models that are
readable by software programs (agents).


Three technologies will bring e
-
commerce to the next generation by
increasing efficiency, compatibility, autono
my, and security:



XML: Create a Semantic Web



Mobile Agents: Automate Electronic

Transactions



Security and Trust: Build a Web of

Trust

The combination of a semantic web, trust, and mobile agent technologies will
enable efficient and secure next
-
generat
ion e
-
commerce in both business
-
to
-
consumer and business
-
to
-
business transactions.


Today’s Web is a vast unstructured mass of information.
HTML was designed
to provide a usable interface for humans, rather than to communicate with
other machines. While HT
ML reflects the structure and limited presentation of
a Web page, it conveys nothing about the meaning of the marked document.
Search engines and software programs have difficulty using information that
is not semantically encoded. Today, several industry
-
focused initiatives have
been formed to work on standards based on
XML

for interoperable
frameworks for e
-
commerce application domains.
For example, XML
-
based
Electronic Data Interchange (EDI) focuses on business
-
to
-
business e
-
commerce for retail transacti
ons, and the supply
-
chain from manufacturer to
wholesaler to retailer. Internet Open Trading Protocol (IOTP) specifies a
consistent, interoperable environment for selling to consumers on the Web.
Rules range from how to offer items for sale, to making paym
ent choices,
delivering products, generating receipts, and resolving problems.


Mobile software agents
are programs that act on behalf of a user or another
program and, for a specified mission, are able to migrate from host to host on
a network. Numerous a
pplications could benefit from mobile agent
technology, such as Internet information retrieval and network management.
However, the greatest potential for mobile agents has been e
-
commerce
applications in which the agents automate and facilitate the phases

of
brokering, negotiation, payment and delivery of a transaction.

In the brokering phase, an agent roams the Web, evaluates available
products, and decides what to buy and from whom to buy, based on a
purchaser’s requirements and preferences. In the next
phase, agents could
negotiate deals autonomously according to a set of user constraints and
strategic guidelines. In the payment and delivery phase, an agent may
automatically fill out a form to place an order, process the order, and track the
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shipment of
the product. So far, the final service and evaluation phase is the
area least explored for mobile agent applications. Nevertheless, mobile
agents may find a promising future in this phase.


Most of the security issues, such as confidentiality, authenticati
on, integrity,
and non
-

repudiation, are addressed by well
-
known cryptographic algorithms
and protocols. However, even if we have a secure channel connecting us to a
party whose identity can be verified, we still have no way to confirm the
trustworthiness

of that party. To meet this challenge, we need a
trust

management mechanism

to manage the histories and reputation of parties
involved in the business to create a web of trust. While the mobile agent
automates the electronic transactions, it also introduc
es new security threats,
such as malicious agents and malicious hosts. A malicious agent is an agent
that performs harmful actions, such as unauthorized access and alteration of
local resources (data, system calls), or an overuse of a host’s local resource
s.
A malicious host is an agent server that attempts to spy out and manipulate
agent code or data and control flow, provide fake system calls, and execute
agent code incorrectly, or to reverse engineer and manipulate agent code and
trade secrets. Therefore
, to provide trustworthiness, it is necessary that both
agent and host are well protected.


At CRCG, a trusted mobile agent environment for e
-
commerce is under
development. The current work develops a trust management system (TMS)
to provide each entity in
volved in an e
-
commerce transaction with a
comfortable and trusted environment. TMS is based on a trust
-
reputation
model that is composed of policies and credentials. Credentials are
statements issued by an entity about another entity, and a policy is a
co
llection of rules for chaining together statements made in credentials. When
combined, credentials and policies can express direct trust in an entity and
delegate that trust to a third party. Moreover, trust in an entity in a certain
domain can be derived
from the reputation of this entity in such a domain.
The reputation, in turn, is calculated and provided by trusted third parties
(TTP).



6.

Integration


Electronic marketplaces for Business
-
to
-
Business (B2B) electronic commerce
bring together many online s
uppliers and buyers. In order to function, they
require the integration of many product catalogs provided by the marketplace
participants. Each individual participant can potentially use his own format to
represent the products in his product catalog. If a

marketplace mediates
between
n
suppliers and
m
buyers, then it must be able to map each of the
n
suppliers’ catalogs into
m
buyers’ formats performing
n
x
m
mappings. The
numbers
n
and
m
may be high enough to make the problem of creating and
maintaining the
se catalog integration rules nontrivial.

A B2B mediator has to integrate both suppliers’ and buyers’ formats to
allow them to do contracting with one another. This makes the problem of
standard integration and interoperation a very important one. A number
of
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high
-
level schema integration approaches exist, proposed by the knowledge
engineering and database communities. They either provide valuable but
abstract guidelines for model integration, logical view, or database
-
specific
algorithms. Given the dominanc
e of XML, e
-
commerce integration technology
must be based on the XML low
-
level integration architecture provided by the
W3C
1
consortium with XSLT and XPath languages.

An address is a simple business concept that occurs very often in e
-
commerce, and it is a
n important part of any B2B mediation system. Unlike
most of the products, the structure of an address and the meaning of its
components are understandable to everybody and this makes the explanation
clear. The integration of address descriptions involves
several interesting
types of problems that also occur in product integration. We present seven
address description standards and point to some problems that arise during
catalog transformation.




xCBL

3.0 developed by Commerce One
2
, Inc. It provides a
compr
ehensive set of standardized XML document formats, allowing
buyers, suppliers and service providers to integrate their existing
systems quickly and efficiently in the electronic marketplaces. The
Document Type Definition (DTD) for an address in the xCBL st
andard
is the following:


<!ELEMENT OrganizationAddress ((AddressType)?, (ExternalAddressID), (POBox)?,

(Street)?, (HouseNumber)?, (StreetSupplement1)?,

(StreetSupplement2)?, (PostalCode)?, (City), (Country),

(Region)?, (District)?, (County)?, (TradingPa
rtnerTimezone)?)>

<!ELEMENT AddressType ((AddressTypeCoded), (AddressTypeCodedOther)?)>




cXML

1.0 developed by a large consortium of companies including
Ariba and Microsoft. cXML is proposed for a similar purpose to xCBL
and it targets document integration

for B2B mediation.
The Document
Type Definition (DTD) for an address in the
cXML
standard is the
following:


<!ELEMENT PostalAddress (DeliverTo*, Street+, City, State?, PostalCode?, Country)>




Internet Open Trading Protocol (IOTP)
was developed within the

Internet Engineering Task Force (IETF
3
) consortium, and it provides a
standard framework for payment operations for Internet commerce. It
is independent of any specific payment system. IOTP provides the
data structures and communication protocols for paym
ent transactions:
purchase, refund, authentication, deposit, and other protocols that
occur in electronic commerce. Security, authentication, and digital
signatures are its main concerns. The DTD for an address in IOTP
standard is the following:


<!ELEMENT

PostalAddress EMPTY>

<!ATTLIST PostalAddress


xml:lang NMTOKEN #IMPLIED


AddressLine1 CDATA #IMPLIED


AddressLine2 CDATA #IMPLIED


CityOrTown CDATA #IMPLIED


StateOrRegion CDATA #IMPLIED

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PostalCode CDATA #IMPLIED


Country CDATA #IMPLIED


LegalLocation (T
rue | False) "False"

>




Open Applications Group Integration Specification (OAGIS)
provides data structures, messaging formats and protocols for
business integration. OAGIS defines a vocabulary of business terms
and more than 90 different types of business
documents can be
exchanged. The DTD for an address in OAGIS standard is the
following:


<!ELEMENT ADDRESS (ADDRLINE*, ADDRTYPE?, CITY?, COUNTRY?, COUNTY?,
DESCRIPTN?, FAX*, POSTALCODE?, REGION?, STATEPROVN?, TAXJRSDCTN?,
TELEPHONE*, URL?, USERAREA?)>




Real

Estate Data Interchange Standard (RETS) defines the
interchange of real estate information. It defines a standard interface
by which a client program may communicate with a property or other
real estate data server. The specification defines a protocol fo
r
implementing transactions, and incorporates an XML specification for
general
-
purpose interchange. It also provides a compressed data
interchange format and specification to allow the interchange of
machine
-
interpretable property information. The data str
uctures for the
interchange are defined in the
Real Estate Transaction Markup
Language (RETML)
, where the DTD for an address is the following:



<!ELEMENT MailingAddress (StreetAddress)>

<!ELEMENT StreetAddress ((StreetNumber?, BoxNumber?, StreetDirPrefix?
, StreetName,
StreetAdditionalInfo?, StreetDirSuffix?, StreetSuffix?, UnitNumber?, City?,
StateOrProvince?, Country?, PostalCode?, CarrierRoute?) | Unstructured)>




United Nation Standard Products and Services Code System
(UNSPSC), is a hierarchical standar
d classification with five levels. The
levels allow users to search products more precisely, because
searches will be confined to logical categories and eliminate irrelevant
hits, and it allows managers to perform expenditure analysis on
categories that ar
e relevant to the company’s situation. Each level
contains a two
-
character numerical value and a textual description as
follows:


XX
Segment

The logical aggregation of families for analytical purposes


XX
Family

A commonly recognized group of inter
-
relate
d commodity categories


XX
Class

A group of commodities sharing a common use or function


XX
Commodity

A group of substitutable products or services


XX
Business Function

The function performed by an organization in support of the commodity




Ecl@
ss is a standard for information exchange and is characterized by
a 4
-
level hierarchical classification system with a key
-
word register of
12,000 words. Ecl@ss maps market structure for industrial buyers and
supports engineers at development, planning and
maintenance.
Through the access either via the hierarchy or over the key words both
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the expert as well as the occasional user can navigate in the
classification.
A unique feature of ecl@ss is the integration of attribute
lists for the description of materi
al and service specifications.


The representations of the same concept, the address, differ in each catalog.
Product description can be encoded in XML with different ways of using XML
tags, i.e. product features can be represented with XML attributes or w
ith
XML elements. Conceptually equal product properties can be encoded with
XML elements with different names. The elements marked up with the same
XML tags can have different semantics. The order of tags is also important in
XML. Finally, some product pro
perties can be described with different
granularity level as required by the application.




6.1.

Unified Catalog


Introduction of a mediating catalog, which is called the
Unified Catalog
(the
UC), only requires the marketplace to perform mapping between each
s
upplier or buyer catalog and the UC, and therefore requires only
n
+
m
mappings instead of
n
x
m
.















For selecting the elements for inclusion in the UC, there are two opposing
strategies
:



The unified catalog stores the minimum core number of attrib
utes for
each product. The UC can change if we add a new catalogue. The
addition of a more detailed catalog will not change the UC, but the
addition of a less detailed catalog will reduce the granularity level of
the UC. As a result, this strategy bounds t
he granularity level of the UC
to the less detailed catalog, which is unacceptable for most B2B
systems.


Integration with
n
+
m
rules


Integration with
n
x
m

rules


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The unified catalog stores the maximum possible number of attributes.
The UC can change if we add a new catalogue. The addition of a new
catalog that

is less detailed than the UC will not influence the latter.
Addition of a more detailed catalog will require updates to the UC so
that it will not be less detailed than the former.




The second strategy
assumes that the UC is at least as detailed as any

other
catalog. This strategy establishes the main direction, but it may be reasonable
to incorporate a number of exceptions. In the address example, the IOTP
standard partitions street information into
AddressLine1
and
AddressLine2
fields, while other cat
alogs partition it as a
Street
name and a
House
number
as presented in the UC, as we will show later. In this case the partitioning of
information between
AddressLine1
and
AddressLine2
is not defined, and
AddressLine1
is not required to be equal to
Street
and
AddressLine2
to
House
. A user of the IOTP standard can freely partition his street and house
information between these address lines. Weak defined semantics is the
reason to not include redundant elements into the UC. Mapping between
different standard
s has the following features:



The catalogs contain a kernel of well
-
mapped elements that are
present in all catalogs and represent the most important features of the
entity described.



The catalogs contain a number of mappings between rarely used
elements t
hat represent the features that are important for one agent
but not for others and which may be included in the descriptions.



The catalogs contain a jumble of ill
-
defined and badly shaped
concepts, which are grouped and mapped in one concept of the UC.



6.2.

Mapping Rules


Mapping rules translate the descriptions between two catalog formats (C1
and C2), one of which is the UC.

Four types of mapping between the
attributes of C1 and C2 are possible:




One
-
to
-
one
mapping is the simplest and most common type of
map
ping between the elements of C1 and C2. It occurs when the
element of C1 has a semantic equivalent in C2, i.e. element
Region
in
the xCBL standard is equivalent to
StateOrRegion
in IOTP, to
REGION
in OAGIS, to
StateOrProvince
in RETML, and to
Province
in t
he UC.
Translation rules in this case are quite simple. If the element is
encoded by an XML element in both C1 and C2, then the rule can be
expressed as follows (from RETML to UC):

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<xsl:for
-
each select="StreetAddress">



<Province><xsl:value
-
of select="St
ateOrProvince"/></Province>



</xsl:for
-
each>




Many
-
to
-
one
mapping occurs when two or more elements from C1
have to be translated into one element in C2. The
Street
and
House
elements in the UC must be translated into the element
ADDRLINE
in
OAGIS. This ca
n be done by means of XSLT in the following way:


<xsl:for
-
each select="address">

<ADDRLINE><xsl:value
-
of select="Street"/>, <xsl:value
-
of select="House"/>

</ADDRLINE>



</xsl:for
-
each>


This will map a pair (
Street
,
House
) of UC elements into the followin
g
OAGIS record:


<ADDRLINE>De Boelelaan, 1081a</ADDRLINE>




One
-
to
-
many
mapping occurs when an element in C1 has to be
translated into several elements in C2.
ADDRLINE
in OAGIS
semantically corresponds to the pair of attributes
Street
and
House
in
the UC. X
SLT language provides the means to represent mapping on
the level of XML elements and attributes, as well as possibilities of
analyzing text inside an element in order to split the element into two or
more pieces. For example, in the following fragment of
an OAGIS
address it is assumed that
ADDRLINE
contains street name separated
from the following house number by a comma:


<ADDRLINE>De Boelelaan, 1081a</ADDRLINE>


First
ADDRLINE
is split into a pair of XML elements:


<ADDRESS>

<ADDRLINE>

<STREET>De Boelela
an</STREET>

<HOUSE>1081a</HOUSE>

</ADDRLINE>



</ADDRESS>





This can be done using the following XSLT rule:



<STREET>


<xsl:variable name="addrline" select="ADDRLINE"/>


<xsl:value
-
of select="substring
-
before($addrline,',')"/>

</ STREET >

<HOUSE>

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<xsl:
variable name="addrline" select="ADDRLINE"/>


<xsl:value
-
of select="substring
-
after($addrline,', ')"/>

</ HOUSE >





Many
-
to
-
many
mapping occurs when a piece of a description is
spread over several elements without evident partitioning of
information betwee
n them.
Street
,
House
, and
PObox
elements of the
UC which maps into xCBL and RETML, correspond to the pair
AddressLine1
,
AddressLine2,

in IOTP without any indication where
street, house, and postbox information should be stored within these
two address lin
es. Mapping of a structured UC record into a less
structured IOTP record can be done straightforwardly:


<xsl:for
-
each select="address">

<AddressLine1><xsl:value
-
of select="Street"/>

<xsl:value
-
of select="House"/></AddressLine1>

<AddressLine2>P.O. Box <xsl
:value
-
of select="PObox"/> </AddressLine2>



</xsl:for
-
each>


The ratio of the reverse mappings from the UC into the individual catalog
reflects the partitioning of the straight mappings presented in the following
table:



xCBL to UC

IOTP to UC

OAGIS to UC

RETML to UC

Ratio

1:1

11

7

12

9

89%

1:
n

0

0

1

0

2%

N
:1

1

0

1

1

7%

N
:
n

0

1

0

0

2%


Most of the rules (89%) represent one
-
to
-
one mappings, while the other types
only appear in special cases, once or twice for each catalog standard.


7.

Economic Impact of
Evolving Semantic Web

7.1.

E
-
Commerce at Present

Information asymmetries create situations where a better informed buyer gets
the best value. As a specific example in the context of e
-
commerce, we take
the case of an actual price search for a specific model of

a camcorder:
Panasonic PV
-
DV102 Digital Camcorder
.


There are several websites that sell the exactly same product at
different prices. A consumer, new to online purchasing may go to
Amazon

and buy the product for
$
5
99.99. A consumer who is more educated about
internet searches is able to do a quick but detailed search through websites
such as
www.dealtime.com

or
www.pricegrabber.com
. In this mann
er,
they
identify

the same product being sold at
http://www.tristatecamera.com

for a
cost of
$
509.99 and total with shipping for
$
533.22. The total savings is
$66.77. There is a significant gain due to the
information asymmetry, this is
price dispersion. Price dispersion implies that households and firms must
spend time and energy in looking for the best value. Search is considered an
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27

important and costly economic activity. As it is costly it will stop befor
e the
consumer has all the information she needs and may result in poor bargains.

As the opportunity cost

of a search increases with each additional unit
of time, the amount of search will be at the exact point where the marginal
benefit equals the margin
al cost. With an increase in the phenomenon of
price dispersion (i.e. same good, different prices), the search amount
increases.



Thus we see that a problem created by information asymmetry and
price dispersion is that the costly economic activity of sear
ch takes place;
which can be seen as a loss in precious resources as well as
inefficiency

in
the market. Another problem is that consumers do not get the best value for
their money if they place a high value on their time. When this happens, firms
that off
er good quality for the consumer dollars may lose out. They are also
adversely impacted because it takes time for the market to absorb price
reduction information. The current search engines are contributing somewhat

to reduction in information asymmetry;
but because they still require the
consumers to be fairly adept in searches, the information asymmetry still
results in price dispersion. A sampling of the search engines at
http://directory.google.com/Top/Home/Consumer_Information/Price_Compari
sons/?tc=1

indicated
measurable

price dispersion.


7.2.

Semantic E
-
Commerce

Millions of searches (over 300 million) are conducted everyday on the Internet
by people tryi
ng to find what they need. This represents a huge cost in terms
of people hours and an enormous drain of resources. The semantic web will
transform millions of dumb (read “un
-
searchable”) web pages into intelligent,
semantically annotated web pages where s
earch for a particular product or
service will be comprehensive and precise. In near term a fatal blow will be
dealt to competition among search engines as all search engines will give
relatively similar results, in long term agents will replace the search

functions
completely. Price differentials will also be driven down as a result. The
additional advantage possessed by consumers with search engine skills will
disappear while the premium that customer had been hitherto willing to pay
for convenience will
decrease.


Under this scenario, anyone looking for a Panasonic PVDV102 Digital
Camcorder will know that the lowest price available for this product is
$533.22. Consumers who then choose Amazon over
Tristate Camera

will be
consciously paying the additional

$66.67 for conveniences such as customer
service, support, reliability etc.


advantages that Amazon has due to brand
recognition. In this way, through the Semantic web, price dispersion is likely
to decrease significantly. It may not reduce to zero as th
ere will still be a
difference in the perceived quality and reliability of the providers as well as
the value placed on the search time and convenience. The significant
decrease in price dispersion caused by the Semantic Web will increase the
efficiency of

the e
-
market and provide increased utility to consumers and e
-
firms.



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28

8.

Existing Applications and Frameworks

In this section, we are going to present a number of
existing application and
frameworks that have been developed to add semantics to e
-
commerce
sy
stems.

8.1.

KAON

This section we present
KAON

-

the Karlsruhe Ontology and Semantic Web
Tool Suite. KAON is developed jointly within several EU
-
funded

projects and
specifically designed to provide the ontology and metadata infrastructure

needed for building, us
ing and accessing semantics
-
driven applications

on
the Web and on
our

desktop.



The Karlsruhe Ontology and SemanticWeb Tool Suite (KAON) builds
on available resources and provides tools for the
engineering, discovery,
management,

and
presentation

of ontol
ogies and metadata. It establishes a
platform needed to apply Semantic

Web technologies to e
-
commerce and
B2B scenarios. Because of that, important design

goals were robustness and
scalability, since these are key quality factors for any enterprise

applica
tion.



8.1.1.

Requirements

While building semantics
-
based applications within E
-
Commerce, Knowledge
Management,

Web Portals, etc. we have gained insight into application
features that warrant

a success. Based on that experience and in order to
enabling reuse ac
ross projects,

we have decided to build a framework
addressing these issues. An extensive requirement

gathering process was
undertaken to come up with a set of requirements that such

framework must
fulfil. The following key requirements were identified:




A
ccessibility
: A framework should enable loose coupling, allowing
access through

standard web protocols, as well as close coupling by
embedding it into other applications.

This should be done by offering
sophisticated standard APIs.





Consistency:
Consisten
cy of information is a critical requirement of any
enterprise

system. Each update of a consistent ontology must result in a
ontology that is also

consistent. In order to achieve that goal, precise rules
must be defined for ontology

evolution and an evoluti
on service
implementing these rules has to be provided.

Also, all updates to the
ontology must be within transactions assuring the usual

properties of
atomicity, consistency, isolation and durability (ACID).






Concurrency:
It must be possible to access an
d modify information
concurrently.

This may be achieved using transactional proces
sing, where
objects can be modi
fied at most by one transaction at the time.


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Durability
: An almost trivial requirement easily accomplished by reusing
existing

database techno
logy. A sophisticated storage system must offer
facilities for replication:

for often used ontologies redundant copies must
be maintained to address

scalability and availability problems.






Security
: Guaranteeing information security means protecting info
rmation
against

unauthorized disclosure, transfer, modification, or destruction,
whether accidental

or intentional. To realize it, any operation should only
be accessible to properly

authorized agents. Proper identity of the agent
must be reliably establis
hed, by employing

known authentication
techniques. Sensitive data must be encrypted for network

communication
and persistent storage. Finally, means for auditing (logging)

of sensitive
operations should be present.





Reasoning
: Reasoning engines are centra
l components of semantics
-
based applications.

Our tools should have access to those engines which
provide the reasoning

services required to
fulfil

a certain task.






Mapping
: Often multiple ontologies have to be supported by an ontology
system.

This suppo
rt is only complete if means for mapping and mediating
between heterogeneous

ontologies are provided.




Discovery:
We assume that data in the Semantic Web will be distributed.
Therefore

means for ontology
-
focused and intelligent discovery of
metadata are re
quired.

Based on a semantic description of the search
target, the system should be able to

discover relevant information on the
Web.






Internationalization:
The framework should allow users to create
ontologies and

their instances in different languages a
nd should support
non
-
Latin character sets.





Formal ontology
The formal semantics specified by
ontology

must be
unambiguous

and clear.


KAON tries to satisfy these requirements by introducing a
Formal Model for
Ontologies

which out of the scope of this re
port. More information
stand

on
paper [8].


8.1.2.

Conceptual Architecture

In this section we introduce the general architecture that is the basis of
KAON. We

mainly distinguish three layers within our conceptual architecture,
namely the data and

remote service l
ayer, the middleware layer and the
applications and services layer. Figure

below

shows this layered architecture:


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KAON Architecture




i.

Applications and Service Layer:
Application and service clients can be
either
(i)
the

components of the Java
-
Applicati
on
-
based OntoMat application
framework or
(ii)
applications

extending the web
-
based KAON
-
PORTAL and
web site management framework.

All application clients connect with the
middleware layer via KAON API, an

application programming interface
accessing ontolo
gy elements. The API realizes the

application model by
providing a set of object
-
oriented abstractions of ontology elements.

Application clients provide views and controllers for model realized by
KAON

API.



ii.

Middleware Layer:
The primary role of the middl
eware layer is to provide
an abstraction

for ontology access. Its second role is the dynamic
instantiation and delegation of

requests to the underlying external services
layer. The first role is implemented by the

KAON API, which isolates clients
from diff
erent API implementations and provides a

unified interface. For
example, a transient ontology model is provided by implementing

the KAON
API on top of RDF files. This implementation may then be used for
inmemory

processing of ontologies stored in files and

stand
-
alone
deployment of tools.

KAON RDF Server is a data source specialized in
storing RDF data. It allows concurrent

modification, supports transactions
and persistence. Non
-
RDF data sources may

be accessed using other
implementations of the KAON API,
thus creating an ontology

compatible

view of data not in a format according to Semantic Web standards.

The
dynamic instantiation and delegation of requests to services is out of scope
for

this paper. The implementation relies on the framework provided by t
he
Java Management

Extensions (JMX).



iii.

Data and Remote Service Layer:
This layer has several roles. First it
offers access

to physical data stores such as databases or file systems.
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Second it groups external

services such as reasoning engines, the
aforemen
tioned mapping engine etc. and announces

availability to the
middleware layer.



For more details about how
the conceptual architecture has been
implemented
, stand on the paper [8].



8.2.

MOMIS

A marketplace is the place in which the demand and supply of buyer
s and
vendors participating in a business process may meet. Therefore,
marketplaces are virtual communities in which buyers may meet proposals of
several suppliers and make the best choice. So, marketplaces seem to be an
interesting solution for e
-
commerce

actors, because they show products,
distributed by different vendors, but that may be compared since they have
similar classification and they represent comparable products. In the e
-
commerce world, the comparison between different products is blocked due

to the lack of standards describing and classifying them. Numerous proposals
of classification standards have resulted in each supplier describing his own
product in his own way.

The marketplace has to provide an environment using which to
mediate among d
ifferent standards used by the different participant to the
transaction. In this way, each actor of the business process may exchange
information using his own format. Therefore, the need, for B2B and B2C
marketplaces, is to reclassify products and goods a
ccording to different
standardization models.


MOMIS

(
M
ediator envir
O
nment for
M
ultiple
I
nformation
S
ystems) is a
mediator
-
based system aiming to extract and integrate information from
heterogeneous data sources, such as relational, object, semi
-
structured

sources (XML). Starting from source descriptions, the system generates an
integrated global virtual schema of all data sources that is expressed in XML.
MOMIS creates a global virtual schema by using different techniques, and by
creating a common thesauru
s of intra
-

and inter
-
schema relationships, which
defines ontology of the terms used to represent the information provided by
the different sources. The common thesaurus contains intra
-
schema
relationships extracted by using inference techniques, inter
-
sch
ema
relationships obtained using the lexical WordNet system (which identifies the
affinities between inter
-
schema concepts on the basis of their lexicon
meaning) and inter
-
schema relationships explicitly given by the integration
designer. MOMIS also enrich
es the thesaurus using the Artemis system,
which evaluates structural affinities among inter
-
schema concepts and ODB
-
Tools Engine, a tool based on Description Logics, which performs checking
consistency and subsumption computation.

MOMIS follows a “semanti
c approach” to information integration based
on the conceptual schema, or metadata, of the information sources, and on
the mediator architecture. In the MOMIS system, each data source provides a
schema and a global virtual schema of all the sources is obta
ined in a semi
-
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automatical way. The global schema has a set of mapping descriptions

that
specify the semantic mapping between the global schema and the sources
schema.



MOMIS Architecture


The system architecture is composed of functional elements that
c
ommunicate using the CORBA standard. A data model, ODM, and a
language, ODL

are used to describe source schemas. ODL

and ODM

have
been defined as subset of the corresponding ones in ODMG, augmented by
primitives to perform integration. ODL

is a source
-
inde
pendent language and
it is used to describe heterogeneous schemas of data sources. In particular,
ODL

includes the following terminological relationships:



SYN (synonym of) is a relationship defined between two terms t
i

and t
j
where t
i

t
j

that are synonyms
in every involved source.



BT (broader terms) is a relationship defined between two terms t
i

and t
j

where t
i

has a broader more general meaning then t
j
. The opposite of
BT is NT (narrower terms)



RT (related term) is a relationship defined between two terms
t
i

and t
j

that are generally used together in the same context in the considered
sources.

To interact with a specific local source, MOMIS uses a
Wrapper
, which has to
be placed over each source. The wrapper translates metadata descriptions of
a source into

the common ODL

representation. The core of the MOMIS
system is the
Mediator
. The Global Virtual Schema (GSB) module processes
and integrates descriptions received from wrappers to derive the global
shared schema by interacting with different service modul
es, namely ODB
-
Tools, an integrate environment for reasoning on object oriented database
based on Description Logics, WordNet lexical database that supports the
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mediator in building lexicon
-
derived relationships, and ARTEMIS tool that
performs the clusteri
ng operation.


8.3.

SemanticEdge

SemanticEdge has developed a state of the art multilingual natural language
(text and voice) dialog system capable of handling dialogs with humans
wanting to access information, for example, to purchase products and
services. Th
e technology extends naturally to Customer Relations
Management (CRM) and other e
-
business functions. This technology
depends on several distinct technology areas within Artificial Intelligence:
natural language processing, including deep language processi
ng and
statistical analyses; machine learning, including inductive learning; speech
recognition; automated dialog generation, both user and content specific; and
knowledge representation and ontologies.



The system mediates between humans and information.

That is, it
mediates between an information space and a human’s conceptualization of
that information space; for example, between a product space and a
customer’s conceptualization of that product space, and how they will
consequently go about searching a
nd querying that product space. Users
hold negotiations with the system, which is mediating access to the product
spaces, and it will ask questions of them. This requires the system to have
the ability to guide those dialogs according to a representation o
f that product
space. This ability to a large extent is supported by ontologies. Not only
does
the technology

model products objectively, as might be done with a
sophisticated database system, but we also model subjective quality
judgments that consumers t
end to use when conceptualizing the product
space before them. These subjective, ad hoc, categories give the system the
ability to communicate

to the consumer in a human friendly way, in a way that
is, in terms of the ontological commitments made by the sy
stem, similar to
those of the typical customer or user. These human
-
oriented aspects are
further enhanced by other technologies within the system, such as user
models of consumer reaction to the dialog process as it happens.




SemanticEdge has also develo
ped the
sePDC

to enable the acquisition of
product instances. This extensional information has to conform to the
imported ontology, and a number of ontology formats, including F
-
logic, can
be accommodated. Here we are capturing some new instances of the
Co
untry conce
pt from the CIA World Fact
-
book as shown below:


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34


sePDC
: Instances Example



SemanticEdge is among a growing number of companies that offer
specialized technology for carrying out this information extraction task. A
number of trainable and self
-
learning Artificial Intelligence (AI) technologies
are encapsulated inside a single Information Extraction Engine. These AI
technologies can be configured to map any number of different product
catalogue formats onto a single intermediate, predefined prod
uct schema.
From this schema, information can be exported into one or more formalized
representations (including ontology languages). Export involves two basic
steps:




Normalization
: This can simply involve mapping one of a number of
synonyms for a given p
iece of product information onto a single
predefined symbol. It can also involve more complex normalization
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35

rules such as converting numeric attribute values that can be given in
one of a number of units onto a single standard unit.




Generation of Export S
yntax
: Through the attachment of formatting
rules to the intermediate product schema, high flexibility in the export
format can be achieved, and as noted, the information can be output to
ontology languages, such as, for example, F
-
logic.



9.

Conclusion



In

the area of heterogeneous information integration,

which is the core issue
related to semantic e
-
commerce,
many
theoretic projects based on mediator

architecture have been developed.

In addition, the description languages
differentiate according to the re
quirements and the implementation way. As
we presented above, the first step have been made using XML as the basis
language for B2B e
-
commerce services descriptions. Some of XML limitations
have been overcome by RDF and DAML+OIL use.



However, most of the

techniques presented above are still in
research
stage, without implemented tools or frameworks. Standardization and
integration using agents is a real challenge for further work with great interest
for B2B and B2C e
-
commerce lifecycle description improve
ment.


































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36

10.

Related Papers


[1] R.G. Smith.
The Contract Net protocol: High
-
level communication and
control in a distributed problem solver
.



In
Proceedings Computing Systems
, pages 186
-
192, Washington, DC,
1979. IEEE Computer
Society.

[2] UDDI.
Universal Des
cription Discovery Integration.



Technical White Paper, 2000

[3]
P. Klemperer.
Auction theory: a guide to the literature.



Journal of Economic Surveys
, 13(3): 227
-
286, 1999

[4] S. Bechhofer, I.Horrocks, C.Goble, and R.Ste
vens,
OilEd: a reason
-
able
ontology editor for the semantic web
.


In
Working Notes of the 2001 Int. Description Logics Workshop (DL
-
2001),
pages 1
-
9, 2001.

[5] W. Grosso, H. Eriksson, R. Fergerson,
J. Gennari, S. Tu, and M. Musen.
Knowledge Modeling at th
e Millenium


The Design and Evolution of
Protégé.


In
Proceedings of the 12
th

International Workshop on Knowledge
Acquisition, Modeling and Management (KAW ’99), 1999.

[6] I.Horrocks.
FaCT and iFaCT
.


In P.

Lambrix, A.

Borgida, M.

Lenzerini, R.

Möller, a
nd P.

Patel
-
Schneider,
editors,
Proceedings of the International Workshop on Description
Logics (DL'99)
, pages 133
-
135, 1999.

[7] J.

González
-
Castillo, D.

Trastour, and C.

Bartolini.
Description logics for
matchmaking of services
.

In
Proceedings of the KI
-
2001 Workshop on Applications of Description
Logics
, 2001.

[8
]
Erol Bozsak, Marc Ehrig, Siegfried Handschuh, Andreas Hotho, Alexander
Maedche,

Boris Motik, Daniel Oberle, Christoph Schmitz, Steffen Staab,
Ljiljana Stojanovic,

Nenad Stojanovic, Rudi Studer
, Gerd Stumme, York
Sure, Julien Tane, Raphael Volz,

Valentin Zacharias
.


KAON
-
Towards a large scale Semantic Web


Forschungszentrum Informatik FZI, 76131 Karlsruhe,

http://www.fzi.de/wim


Institute AIFB, University of Karlsruhe, 76128 Karlsruhe,

http://www.aifb.uni
-
karlsruhe.de/WBS













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Antonis Misargopoulos, Athina Tziaki



37

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