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Improving search engine query expansion using clustering and indexing based approach

机译:使用基于聚类和索引的方法改善搜索引擎的查询扩展

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In old days, people have become conscious about the consequences of archiving and finding information. With the arrival of computers, it became possible to store huge amount of information; and finding the useful information from images collections which is became a necessity. Out of this necessity in the 1950s, the field of Information Retrieval (IR) was born. The field of information retrieval has matured considerably over the last forty years. Query expansion main objective is to extend the user query with related terms to improvise the search results. It is done to improve the relevance of the documents which are retrieved by the IR systems. In this paper, we propose a Cluster and Indexing based approach for query expansion. We also presents that our proposed mechanism produces better recall and precision.
机译:在过去,人们已经意识到存档和查找信息的后果。随着计算机的到来,存储大量信息成为可能。并从图像收集中找到有用的信息,这成为了必要。出于1950年代的这种必要性,信息检索(IR)领域诞生了。在过去的四十年中,信息检索领域已经相当成熟。查询扩展的主要目的是用相关术语扩展用户查询,以简化搜索结果。这样做是为了提高IR系统检索的文档的相关性。在本文中,我们提出了一种基于聚类和索引的查询扩展方法。我们还提出,我们提出的机制可产生更好的召回率和准确性。

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