基于概念的信息访问

R. Ozcan, Y. Aslandogan
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引用次数: 16

摘要

基于概念的信息访问比基于关键字的访问更有优势。其中一个好处是能够利用概念之间的语义关系来查找相关文档。另一个好处是通过识别概念不匹配来消除不相关的文档。概念是心理结构。单词和短语是概念的语言代表。由于自然语言固有的简洁性,单词可以表示多个概念,不同的单词可以表示相同或非常相似的概念。词义消歧试图利用上下文信息来解决这种歧义。本体的使用有助于识别相关概念及其给出的关键概念的语言代表。而隐性语义分析则试图根据语言的使用模式揭示词和短语之间隐藏的概念关系。在这项工作中,我们通过这两种方法探索基于概念的信息访问的潜力。我们研究在什么情况下基于概念的访问变得可行并改善用户体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Concept-based information access
Concept-based access to information promises important benefits over keyword-based access. One of these benefits is the ability to take advantage of semantic relationships among concepts in finding relevant documents. Another benefit is the elimination of irrelevant documents by identifying conceptual mismatches. Concepts are mental structures. Words and phrases are the linguistic representatives of concepts. Due to the inherent conciseness of natural language, words can represent multiple concepts and different words may represent the same or very similar concepts. Word sense disambiguation attempts to resolve this ambiguity using contextual information. The use of an ontology facilitates identification of related concepts and their linguistic representatives given a key concept. Latent semantic analysis, on the other hand, attempts to reveal the hidden conceptual relationships among words and phrases based on linguistic usage patterns. In this work we explore the potential of concept-based information access via these two methods. We examine under what circumstances concept-based access becomes feasible and improves user experience.
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