Cart (Loading....) | Create Account
Close category search window
 

On the use of fuzzy information retrieval for gauging similarity of Arabic documents

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Alzahrani, S.M. ; Fac. of CS & Info. Sys, Taif Univ., Hawiah, Saudi Arabia ; Salim, N.

As one of the richest human languages in terms of words constructions and diversity of meanings, judging similarity amongst statements in Arabic documents is complex. In this paper, we present a mechanism for gauging similarity of Arabic documents using fuzzy IR model. Similarity degree of two documents is the averaged similarity among statements treated as equal although they have been restructured or reworded. We introduced some fuzzy similarity sets such as near duplicate, very similar, similar, slightly similar, dissimilar and very dissimilar. These similarity sets can be implemented as a spectrum of values ranges from 1 (duplicate) and 0 (different). Our corpus collection has been built in which all stop words were removed and nonstop words were stemmed using typical Arabic IR techniques. The corpora has 100 documents with 4477 statements and 54346 non-stop-word, stemmed words in total. Another 15 query documents with 303 statements and 1620 words were specifically constructed for our test. Experimental results show that fuzzy IR can be used to define the extent documents are similar or dissimilar, where similarity can be mapped to one of the proposed fuzzy sets. The performance of our fuzzy IR system, measured in fuzzy precision and fuzzy recall, shows that it outperforms Boolean IR in retrieving more documents that have similar content but with different synonyms.

Published in:

Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on the

Date of Conference:

4-6 Aug. 2009

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.