Domain-Specific Knowledge Acquisition Using WordNet

Roxana Girju, Southern Methodist University

In many knowledge intensive applications, it is necessary to have extensive domain-specific knowledge in addition to general-purpose knowledge. This paper presents a methodology for discovering domain-specific concepts and relationships in an attempt to extend WordNet. The method was tested on five seed concepts selected from the financial domain: interest rate, stock market, inflation, economic growth, and employment. Queries were formed with each of these concepts and a corpus of 1000 sentences/seed was extracted automatically from the Internet and the TREC-8 corpora. The system discovered a total of 362 new concepts and 62 new relationships while working in an interactive mode.


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