Semantic similarity between terms for query suggestion

Mamta Kathuria, Payal, C. K. Nagpal, Neelam Duhan
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引用次数: 5

Abstract

To retrieve semantically related documents with the query submitted by the user has always become a challenging task. An efficient assessment of semantic similarity is of critical importance in the area of information retrieval and web mining so as to associate the query with its associated documents. However their cannot be any accurate measure for semantic similarity as its domain is spread not only over individual words but also on the terms, phrases, sentences, entity and sometime even over whole of the document. To calculate semantic similarity between terms based on synsets a new method is proposed in this paper in which synsets are derived using online resources. The advantage of the proposed work is that, the semantic similarity between terms is calculated that helps in query suggestion or replacement of one query with the most appropriate query.
术语之间的语义相似度用于查询建议
使用用户提交的查询检索语义相关的文档一直是一项具有挑战性的任务。在信息检索和网络挖掘领域,有效的语义相似度评估对于将查询与相关文档关联起来至关重要。然而,语义相似度并不是一个精确的度量,因为语义相似度的范围不仅包括单个单词,还包括术语、短语、句子、实体,有时甚至包括整个文档。本文提出了一种利用在线资源推导同义词集的方法来计算词间语义相似度。该方法的优点是计算了术语之间的语义相似度,有助于查询建议或用最合适的查询替换一个查询。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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