信息检索中基于两级文档排序方法的词义歧义消解

Hyun-Kyu Kang, H. Jeon, Myeong-Cheol Ko, Jinsoo Kim, Kiduk Yang
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引用次数: 2

摘要

词义歧义的消解是信息检索中的一个重要问题。单词可以有多种含义或含义,脱离上下文使用单词在这些含义之间是模棱两可的。互信息是表征一个词与另一个词之间关系的关系度量。为了消除检索文档中的词汇歧义,我们重新评估检索文档的术语与查询术语之间的关系。本文讨论了一种利用互信息的两级文档排序方法来解决信息检索中的词义歧义问题。在第一层,我们根据自动构造的关键字索引检索文档。在第二级,我们使用互信息对检索到的文档重新排序。我们展示了我们的方法在检索的文档中提供了词义歧义的解析。此外,我们还分析了几种公式,并找到了一种消除检索文档中词义歧义的公式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Resolving of Word Sense Ambiguity Using Two-level Document Ranking Method in Information Retrieval
The resolving of word sense ambiguity is one of important problem in information retrieval. Words can have several meanings or senses, and a use of the word out of context is ambiguous between these senses. Mutual information is a relation measure which represents relation between a word and another word. To disambiguate the lexical ambiguity in the retrieved documents, we re-evaluate relation between terms of retrieved document and terms of query. In this paper, we discuss a resolving of word sense ambiguity of information retrieval that is two-level document ranking method using mutual information. At the first level, we retrieve documents based on an automatically constructed keyword index. At the second-level, we reorder the retrieved documents using mutual information. We show that our method provides a resolving of word sense ambiguity in the retrieved documents. Also, we analyze several formulas and found a formula which to disambiguate the word sense ambiguity in the retrieved documents.
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