Multi-Phase Reasoning of

wrendeceitInternet and Web Development

Oct 21, 2013 (3 years and 5 months ago)

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Multi
-
Phase Reasoning of
temporal semantic knowledge

Sakirulai

O.
Isiaq

and
Taha

Osman

School of Computer and Informatics

Nottingham Trent University

Nottingham United Kingdom.

Outlines


Dynamics of information (the web)


Application example


Possible solution


Semantic Web


Simple semantic query


Challenges


Proposed solution


Multiphase Reasoning Framework


Multi
-
phase Temporal reasoning Model


Future work and Issues of MPR Framework
.


Dynamics of web Information


Collection of globally distributed text, files,
media documents and network links.


The world wide web information is so
enormous that personalised information is
now required by individual user.


Personalising information may required
individual user’s context(s)in service(s)
recommendation.


One context might depend on the other in
event of Multi
-
Contexts.



Dynamics of Information (cont.)


A large proportion of this information are
subjected to changes due to their dynamism


This changes are also time
-
critical, which can
be due to the temporal state inherent from
dynamic application domains or increased in
the use of nomadic smart devices capable of
recording real
-
time user context


Time
-
critical temporal information requires
automation.


Application Example


Consider a context
-
aware system using
obtained information from multiple sources
(
e.g

geonames
) and locally sourced event
from the service provider application domain
in
-
line with user’s device information to enrich
contextual data on services offer to the users.

Solution


Solution to such application involves two
stages:


Information exploration:


Exploring the temporal information in the service’s
provider domain with regards to relevant information
extracted from the user’s device


Exploration the publicly published information in
extracting the relevant part


Match
-
making explored information to
produce adequate service.


Semantic Web


Simply helps in converting current web information
in an form of unstructured and semi
-
structured
documents into web of data


This is done through hierarchical classification and
relationship; i.e. description of concepts, terms, and
relationship within a knowledge domain.


Built on RDF Framework


Semantic web is built on RDF, which uses XML
Syntax, an easy machine understandable language.


Helps to improve
automation

through using machine
understandable meta
-
data.

Semantic web (Cont.)


This advantages of semantic web now encourages people and
organisation to publicly publish semantically tagged
information.


Lots of the

current information
are time
-
critical due to:


Temporal state inherent in dynamic application domain
e.g. media, news etc.


Increased demand in the used of nomadic smart devices
that are capable of recording real
-
time devices.


Hence, representing
and interlinking time
-
critical multi
-
domain and location
-
aware information play a critical role
when enabling and enacting such data.

Simple Query Information Retrieval


Such information should be retrieved using a
simple Query as below:


Select ?service , ?location

Where

{

?service


cas:relates



?context

?context


rdf:type



cas:Context

}

Challenges


Exploration and match
-
making of publicly source
information and application domain information


Representing time
-
critical information semantically.


Temporal Context definition and identification


Multi reasoning and classification of inter
-
dependent
contexts.


Comprehensive coupling and handling of multi contextual
information in service recommendation.


Multi
-
Phase reasoning of inter
-
dependent multi
-
contextual information.

Proposed Solution

Multi
-
Phase Reasoning Framework


We proposed a multi
-
phase frame work in
conjunction with the current semantic technology to
deal with the problems such as:


Abstraction (temporal knowledge abstraction)


Supplementary reasoning of extracted temporal
multi
-
contextual information.


Alignment and match
-
making the extracted
temporal information.


It wraps the service provider application domain in
relating users information and published data.


Multi
-
phase Temporal Reasoning
Model


Multi
-
phase temporal reasoning model


Adoption of modelling techniques to overcome
the owl limitation through temporal concept
isolation


The introduction Validity domain (an element of
time) used to


The introduction of Context domain (concepts to
for the aggregation of context and segregation of
static and temporal contexts)

MPR Framework issues and future
work


Issues anticipated for MPR framework include:


Scalability


Performances issue for large scale datasets


Quality of services


Anticipated solution applying Aristotle concepts of
change


The generation of a substance is the perishing of the other
and vice
-
versa


We are trying to apply this concept contextual work i.e. the
generation of one context can be the perishing of the
other, then check the effect the performance of the system


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