扩展布尔信息检索:基于语言变量的模糊模型

Gloria Bordogna, P. Carrara, G. Pasi
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引用次数: 15

摘要

在信息检索系统中,用户对信息请求的模糊性主要通过使用数字权重来管理。在检索模型的正式定义中,在查询语言中使用语言描述符来表示某个术语在所需文档中必须具有的重要性,并将检索到的文档标记为相关类。通过将数字权重附加到术语上,用户可以提供该术语在所搜索的文档中的重要性的定量描述。如果权重的引入减少了查询公式中的模糊性,那么数字权重的使用需要清楚地了解它们的语义,并将模糊概念转换为精确的数值。基于这些问题,从现有的加权布尔检索模型出发,作者在模糊集理论中形式化了一个新的模型,该模型允许对用户查询进行解释,其中每个术语附加一个语言描述符。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending Boolean information retrieval: a fuzzy model based on linguistic variables
In information retrieval systems the vagueness in user requests for information is mainly managed by the use of numeric weights present the formal definition of a retrieval model in which linguistic descriptors are used in the query language both to express the importance that a term must have in the desired documents and to label the retrieved documents in relevance classes. By attaching a numeric weight to a term, a user provides a quantitative description of the importance of that term in the documents sought. If the introduction of weights reduces the vagueness in query formulation, the use of numeric weights requires a clear knowledge of their semantics and the translation of a fuzzy concept in a precise numeric value. Based on these problems and starting from an existing weighted Boolean retrieval model, the authors formalize within fuzzy set theory a new model that allows the interpretation of a user query in which a linguistic descriptor is attached to each term.<>
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