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

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 docum...

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Main Authors: Mohammed Alzahrani, Salha, Salim, Naomie
Format: Book Section
Published: Institute of Electrical and Electronics Engineers 2009
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Online Access:http://eprints.utm.my/id/eprint/13027/
http://dx.doi.org/10.1109/ICADIWT.2009.5273835
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Institution: Universiti Teknologi Malaysia
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spelling my.utm.130272011-07-14T01:26:30Z http://eprints.utm.my/id/eprint/13027/ On the use of fuzzy information retrieval for gauging similarity of arabic documents Mohammed Alzahrani, Salha Salim, Naomie QA75 Electronic computers. Computer science 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. Institute of Electrical and Electronics Engineers 2009 Book Section PeerReviewed Mohammed Alzahrani, Salha and Salim, Naomie (2009) On the use of fuzzy information retrieval for gauging similarity of arabic documents. In: 2nd International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2009. Institute of Electrical and Electronics Engineers, New York, 539 -544. ISBN 978-142444457-1 http://dx.doi.org/10.1109/ICADIWT.2009.5273835 doi: 10.1109/ICADIWT.2009.5273835
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Mohammed Alzahrani, Salha
Salim, Naomie
On the use of fuzzy information retrieval for gauging similarity of arabic documents
description 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.
format Book Section
author Mohammed Alzahrani, Salha
Salim, Naomie
author_facet Mohammed Alzahrani, Salha
Salim, Naomie
author_sort Mohammed Alzahrani, Salha
title On the use of fuzzy information retrieval for gauging similarity of arabic documents
title_short On the use of fuzzy information retrieval for gauging similarity of arabic documents
title_full On the use of fuzzy information retrieval for gauging similarity of arabic documents
title_fullStr On the use of fuzzy information retrieval for gauging similarity of arabic documents
title_full_unstemmed On the use of fuzzy information retrieval for gauging similarity of arabic documents
title_sort on the use of fuzzy information retrieval for gauging similarity of arabic documents
publisher Institute of Electrical and Electronics Engineers
publishDate 2009
url http://eprints.utm.my/id/eprint/13027/
http://dx.doi.org/10.1109/ICADIWT.2009.5273835
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