短文本查询扩展中扩展词间的关联性挖掘
首发时间:2013-12-19
摘要:本文针对经典查询扩展算法展开深入调研,分析了现阶段查询扩展方法所存在的缺陷。提出了一种基于词激活力模型的扩展词间关联性挖掘算法。利用词激活力模型中词间亲密度,计算扩展词间的关联性,得到扩展词对,并利用扩展词对进行查询重构。实验数据说明,词激活力模型可以很好的对于词间关系建模,同时扩展词对可以有效的减少因扩展词引起的信息偏移,同时提升检索系统的整体性能。
关键词: 信息检索 查询扩展 扩展词对 词激活力模型 查询重构
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Relevance exploration between short text query expansion words
Abstract:This paper mainly focuses on the relationship between expansion words. Based on the analysis of traditional query expansion models, we find that query expansion sometimes give rise to information shifting. In order to improve this situation, we propose a method to explore the relevance between expansion words using word activation forces model (WAF). We generate expansion-words-pairs by calculating affinity of different expansion words and reconstruct query with these pairs of words. According to experiment data, it's a wise choice using WAF modeling the relationship between words and pairs of expanded words can effectively reduce shift caused by expansion terms while enhancing the overall performance of the retrieval system.
Keywords: Information Retrieval Query Expansion Expansion-words-pairs Word Activation Forces Query Reconstruction
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