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AuthorShaban, Khaled B.
Available date2022-12-21T10:01:45Z
Publication Date2009
Publication NameJournal of Software
ResourceScopus
URIhttp://dx.doi.org/10.4304/jsw.4.5.391-404
URIhttp://hdl.handle.net/10576/37487
AbstractConventional document mining systems mainly use the presence or absence of keywords to mine texts. However, simple word counting and frequency distributions of term appearances do not capture the meaning behind the words, which results in limiting the ability to mine the texts. In this paper, the application of a semantic understandingbased approach to mine documents is presented. The approach is based on semantic notions to represent text, and to measure similarity between text documents. The representation scheme reflects existing relations between concepts and facilitates accurate similarity measurements that result in better mining performance. A document mining process, namely semantic document clustering, is investigated and tackled in various ways. The proposed representation scheme along with the proposed similarity measure were implemented as vital components of a mining system. The approach has enabled more effective document clustering than what conventional techniques would provide. The experimental work is reported, and its results are presented and analyzed. 2009 ACADEMY PUBLISHER.
Languageen
PublisherAcademy Publisher
SubjectDocument clustering
Document mining
Semantic understanding
Similarity measure
Text representation
TitleA semantic approach for document clustering
TypeArticle
Pagination391-404
Issue Number5
Volume Number4
dc.accessType Abstract Only


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