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Báo cáo khoa học: "Evaluation of Semantic Clusters"

Semantic clusters of a domain form an important feature that can be useful for performing syntactic and semantic disambiguation. Several attempts have been made to extract the semantic clusters of a domain by probabilistic or taxonomic techniques. However, not much progress has been made in evaluating the obtained semantic clusters. This paper focuses on an evaluation mechanism that can be used to evaluate semantic clusters produced by a system against those provided by human experts. | Evaluation of Semantic Clusters Rajeev Agarwal Mississippi State University Mississippi State MS 39762 USA rajeev@cs.msstate.edu Abstract Semantic clusters of a domain form an important feature that can be useful for performing syntactic and semantic disambiguation. Several attempts have been made to extract the semantic clusters of a domain by probabilistic or taxonomic techniques. However not much progress has been made in evaluating the obtained semantic clusters. This paper focuses on an evaluation mechanism that can be used to evaluate semantic clusters produced by a system against those provided by human experts. 1 Introduction1 Most natural language processing NLP systems are designed to work on certain specific domains and porting them to other domains is often a very timeconsuming and human-intensive process. As the need for applying NLP systems to more and varied domains grows it becomes increasingly important that some techniques be used to make these systems more portable. Several researchers Lang and Hirschman 1988 Rau et al. 1989 Pustejovsky 1992 Grishman and sterling 1993 Basili et al. 1994 either directly or indirectly have addressed issues that assist in making it easier to move an NLP system from one domain to another. One of the reasons for the lack of portability is the need for domain-specific semantic features that such systems often use for lexical syntactic and semantic disambiguation. One such feature is the knowledge of the semantic clusters in a domain. Since semantic classes are often domain-specific their automatic acquisition is not trivial. Such classes can be derived either by distributional means or from existing taxonomies knowledge bases dictionaries thesauruses and so on. A prime example of the latter is WordNet which has been used to 1The author is currently at Texas Instruments and all inquiries should be addressed to rajeev@csc.ti.com. provide such semantic classes Resnik 1993 Basili et al. 1994 to assist in text .