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Supporting web query expansion efficiently using multi-granularity indexing and query processing

机译:使用多粒度索引和查询处理有效地支持Web查询扩展

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The problem of word mismatch in information retrieval (IR) occurs because users often use different words to describe concepts in their queries than authors use to describe the same concepts in their documents. Query expansion is used to deal with the mismatch between author and user vocabularies. To support query expansion, indices on words related by lexical semantics and syntactical co-occurrence need to be maintained. Two issues become paramount in supporting query expansion f the size of index tables and the query processing overhead. In this paper, we propose to use the notion of multi-granularity for more efficient indexing and query processing while the same degrees of precision and recall are maintained. We also describes extensions of this technique to handle: (1) query relaxation to handle words with multiple senses and with other semantic relationships; (2) progressive processing of queries with top N results and (3) progressive processing of queries with specification of the importance of each keyword.
机译:出现信息检索(IR)中的单词不匹配的问题是因为用户在查询中使用的单词描述概念与作者在文档中描述相同概念的单词不同。查询扩展用于处理作者和用户词汇之间的不匹配。为了支持查询扩展,需要维护与词汇语义和句法共现相关的单词的索引。支持索引表大小和查询处理开销的两个问题对于支持查询扩展至关重要。在本文中,我们建议使用多粒度概念来更有效地建立索引和查询处理,同时保持相同程度的精度和查全率。我们还描述了该技术的扩展,以处理:(1)查询松弛,以处理具有多种意义和其他语义关系的单词; (2)对前N个结果的查询进行渐进处理,以及(3)对每个关键字的重要性进行说明的查询进行渐进处理。

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