Ambiguity in text mining

被引：0
|
作者：
Al Fawareh, Heiab Ma'azer [1 ]
Jusoh, Shaidah [1 ]
Osman, Wan Rozaini Sheikh [1 ]
机构：
[1] Univ Utara Malaysia, Coll Arts & Sci, Grad Dept Comp Sci, Sintok 06010, Kedah, Malaysia
来源：
2008 INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION ENGINEERING, VOLS 1-3 | 2008年
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
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.
引用
收藏
页码：1172 / 1176
页数：5
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