A Collaborative Decentralized Approach to Web Search

toadspottedincurableInternet και Εφαρμογές Web

4 Δεκ 2013 (πριν από 3 χρόνια και 11 μήνες)

99 εμφανίσεις

A Collaborative Decentralized

Approach to Web Search

Abstract:


Most explanations of the user behavior while interacting

with the web are based
on a top
-
down approach, where

the entire Web, viewed as a vast collection of pages and

interconnection

links, is used to predict how the users interact with

it. A prominent example of
this approach is the random
-
surfer

model, the core ingredient behind Google’s Page

Rank. This
model

exploits the linking structure of the Web to estimate the
percentage

of web surfers
viewing any given page. Contrary to the

top
-
down approach, a bottom
-
up approach starts from
the user

and incrementally builds the dynamics of the web as the result of

the users’ interaction
with it. The second approach has not bei
ng

widely investigated, although there are numerous
advantages over

the top
-
down approach regarding (at least) personalization and

decentralization
of the required infrastructure for web tools. In

this paper, we propose a bottom
-
up approach to
study the we
b

dynamics based on web
-
related data browsed, collected, tagged,

and semi
-
organized by end users.


Our approach has been materialized

into a hybrid bottom
-
up search engine that
produces search

results based solely on user provided
web
-
related data and their

sharing among
users.

We conduct an extensive experimental study

to demonstrate the qualitative and
quantitative characteristics of

user generated web
-
related data, their strength, and weaknesses

as
well as to compare the search r
esults of our bottom
-
up search

engine with those of a traditional
one. Our study shows that a

bottom
-
up search engine starts from a core consisting of the most

interesting part of the Web (according to user opinions) and incrementally

(and measurably)
impr
oves its ranking, coverage, and

accuracy. Finally, we discuss how our approach can be
integrated

with Page

Rank, resulting in a new page ranking algorithm that

can uniquely combine
link analysis with users’ preferences
.


Hardware Requirements:


Processor
Speed

:

P4 (Above 2GHZ)


RAM



:

256MB


Hard Disk Drive

:

40GB


Mouse



:

Optical Mouse with Scroll


Keyboard


:

Multimedia Keyboard

Software Requirements:


Application Type

: Windows application


Front
-
End


:

Microsoft
Visual Studio

2005


Coding Language

:


C#
.NET

Back End


:

XML





Existing System:




The regular expressions then we will find that patterns are more powerful, but slower in
matching.



However this information is often scattered among many web servers and hosts, using
many different formats.



All works are done by manually like searching process and getting the result.



Will not get the all related information in a single page and effective manner.


Proposed System:




The system propose a search
engine should

meet in both search intention identification
and relevance oriented ranking for
search results
.




User using these three ambiguity in proposed system they are

Ambiguity 1:

A keyword can appear both as an XML tag name and as a text value of
some other nodes.

Ambiguity 2:

A keyword can appear as the text values of different types of XML nodes
and carry different meanings.


Ambiguity 3:

A keyword can appear as an XML tag name
in different contexts and
carry different meanings.



In particular, we define XML TF and XML DF, based on which we design formulae to
compute the confidence level of each candidate node type to be a search for/search via
node, and further propose a novel
XML TF*IDF similarity ranking scheme to capture the
hierarchical structure of XML data.



The system integrates concept
-
level search and ontology
-
level search by recommending
ontologies and allowing filtering concepts with ontologies.



A

mode of interaction t
hat helps users quickly find desired concepts and ontologies as
well as a supportive combined inverted index structure



A

method of constructing virtual documents of concepts that includes the names of
associated properties and related entities
.



We have als
o performed a usability evaluation and compared various aspects of five
accessible ontology search engines.