A New Similarity Measure for Automatic Construction of the Unknown Word Lexical Dictionary

被引:12
|
作者
Hwang, Myunggwon [1 ]
Kim, Pankoo [1 ]
机构
[1] Chosun Univ, Dept Comp Engn, Kwangju, South Korea
关键词
Data Dictionary; Data Mining; Data Semantics; Information Richness; Knowledge Acquisition; Knowledge Base;
D O I
10.4018/jswis.2009010102
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article deals with research that automatically constructs a lexical dictionary of unknown words. The lexical dictionary has been usefully applied to various fields for semantic information processing. It has limitations in which it only processes terms defined in the dictionary. Under this circumstance, the concept of "Unknown Word (UW)" is defined. UW, in this research, is considered a word not defined in WordNet. Here is where a new method to construct UW lexical dictionary through inputting various document collections scattered on the web is proposed. We grasp related terms of UW and measure semantic relatedness (similarity) between an UW and a related term(s). The relatedness is obtained by calculating both probabilistic relationship and semantic relationship. This research can extend UW lexical dictionary with an abundant number of UW. It is also possible to prepare a foundation for semantic retrieval by simultaneously using the UW lexical dictionary and WordNet. [Article copies are available for purchase from InfoSci-on-Demand.com]
引用
收藏
页码:48 / 64
页数:17
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