Paper: Identification of Domain-Specific Senses in a Machine-Readable Dictionary

ACL ID P11-2097
Title Identification of Domain-Specific Senses in a Machine-Readable Dictionary
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

This paper focuses on domain-specific senses and presents a method for assigning cate- gory/domain label to each sense of words in a dictionary. The method first identifies each sense of a word in the dictionary to its cor- responding category. We used a text classifi- cation technique to select appropriate senses for each domain. Then, senses were scored by computing the rank scores. We used Markov Random Walk (MRW) model. The method was tested on English and Japanese resources, WordNet 3.0 and EDR Japanese dictionary. For evaluation of the method, we compared English results with the Subject Field Codes (SFC) resources. We also compared each En- glish and Japanese results to the first sense heuristics in the WSD task. These results suggest that identification of domain-specific senses (I...