文章基本信息

标题：Feature-Based Relation Classification Using Quantified Relatedness Information
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作者：Huang, Jin-Xia ; Choi, Key-Sun ; Kim, Chang-Hyun 等
期刊名称：ETRI Journal
印刷版ISSN：1225-6463
电子版ISSN：2233-7326
出版年度：2010
卷号：32
期号：3
页码：482-485
DOI：10.4218/etrij.10.0209.0353
语种：English
出版社：Electronics and Telecommunications Research Institute
摘要：Feature selection is very important for feature-based relation classification tasks. While most of the existing works on feature selection rely on linguistic information acquired using parsers, this letter proposes new features, including probabilistic and semantic relatedness features, to manifest the relatedness between patterns and certain relation types in an explicit way. The impact of each feature set is evaluated using both a chi-square estimator and a performance evaluation. The experiments show that the impact of relatedness features is superior to existing well-known linguistic features, and the contribution of relatedness features cannot be substituted using other normally used linguistic feature sets.
关键词：Relation classification;feature selection;semantic relatedness;probabilistic relatedness;feature-based