Learning Chinese Attribute Nouns Using Lexico-Syntactic Patterns

摘要：

Lexical knowledge sources or lexical ontologies are very important to the knowledge grid and semantic computing. Attribute information are key elements for defining concepts in lexical sources. This paper explores the idea of creating corpus-based attribute classifiers using lexico-syntactic patterns. Two novel attribute classifiers are proposed, one is a likelihood ratio classifier using hand-coded lexicosyntactic patterns, the other is a maximum entropy (ME) classifier exploiting automatic extracted patterns. The performance of the method is compared to both the direct pattern matching approach and the human performance, which indicates that the proposed method for attribute learning is very effective.

作者: Jinglei Zhao Hui Liu Yanbo Gao Ruzhan Lu

作者单位: Department of Computer Science Shanghai Jiao Tong University 800 Dongchuan Road Shanghai, China

会议类型: 国际会议

会议名称: 2007年第三届语义和知识网格国际会议(Third International Conference on Semantics,Knowledge,and Grid)(SKG 2007)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-10-29（万方平台首次上网日期，不代表论文的发表时间）