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頁籤選單縮合
題 名 | Adaptive Word Sense Disambiguation Using Lexical Knowledge in a Machine-readable Dictionary |
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作 者 | Chen,Jen Nan; | 書刊名 | International Journal of Computational Linguistics & Chinese Language Processing |
卷 期 | 5:2 2000.08[民89.08] |
頁 次 | 頁1-42 |
分類號 | 310.153 |
關鍵詞 | 字彙知識; 語意; Word sense disambiguation; Machine-readable dictionary; Semantics; |
語 文 | 英文(English) |
英文摘要 | This paper describes a general framework for adaptive conceptual word sense disambiguation. The proposed system begins with knowledge acquisition from machine-readable dictionaries. Central to the approach is the adaptive step that enriches the initial knowledge base with knowledge gleaned from the partial disambiguated text. Once the knowledge base is adjusted to suit the text at hand, it is applied to the text again to finalize the disambiguation decision. Definitions and example sentences from the Longman Dictionary of Contemporary English are employed as training materials for word sense disambiguation, while passages from the Brown corpus and Wall Street Journal (WSJ) articles are used for testing. An experiment showed that adaptation did significantly improve the success rate. For thirteen highly ambiguous words, the proposed method disambiguated with an average precision rate of 70.5% for the Brown corpus and 77.3% for the WSJ articles. |
本系統中英文摘要資訊取自各篇刊載內容。