DocumentCode
2326440
Title
Ambiguity in text mining
Author
Al Fawareh, H.M. ; Jusoh, Shaidah ; Osman, Wan Rozaini Sheikh
Author_Institution
Grad. Dept. of Comput. Sci., Univ. Utara Malaysia, Kedah
fYear
2008
fDate
13-15 May 2008
Firstpage
1172
Lastpage
1176
Abstract
Text Mining tasks include text categorization, text clustering, concept/entity extraction, document summarization, and entity relation modeling. In this paper, the focus is given to concept/entity extraction only. The major challenging issue in extracting concept/entity from texts is natural language words are always ambiguous. Up to now, not much research in text mining especially in concept/entity extraction has focused on the ambiguity problem. This paper addresses ambiguity issues in natural language texts, and presents a new technique for resolving ambiguity problem in extracting concept/entity from texts. The technique is developed by applying possibility theory, fuzzy set, and knowledge about the context to lexical semantics.
Keywords
entity-relationship modelling; information retrieval; natural language processing; text analysis; ambiguity problem; concept extraction; document summarization; entity extraction; entity relation modeling; natural language words; text categorization; text clustering; text mining; Data mining; Fuzzy set theory; Fuzzy sets; Humans; Natural languages; Possibility theory; Text categorization; Text mining; Text processing; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Communication Engineering, 2008. ICCCE 2008. International Conference on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4244-1691-2
Electronic_ISBN
978-1-4244-1692-9
Type
conf
DOI
10.1109/ICCCE.2008.4580791
Filename
4580791
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