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
Link To Document :
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