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首页> 外文会议>International Conference on String Processing and Information Retrieval(SPIRE 2004); 20041005-08; Padova(IT) >Processing Conjunctive and Phrase Queries with the Set-Based Model
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Processing Conjunctive and Phrase Queries with the Set-Based Model

机译：基于集合的模型处理联合查询和短语查询

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摘要

The objective of this paper is to present an extension to the set-based model (SBM), which is an effective technique for computing term weights based on co-occurrence patterns, for processing conjunctive and phrase queries. The intuition that semantically related term occurrences often occur closer to each other is taken into consideration. The novelty is that all known approaches that account for co-occurrence patterns was initially designed for processing disjunctive (OR) queries, and our extension provides a simple, effective and efficient way to process conjunctive (AND) and phrase queries. This technique is time efficient and yet yields nice improvements in retrieval effectiveness. Experimental results show that our extension improves the average precision of the answer set for all collection evaluated, keeping computational cost small. For the TReC-8 collection, our extension led to a gain, relative to the standard vector space model, of 23.32% and 18.98% in average precision curves for conjunctive and phrase queries, respectively.
机译：本文的目的是提出对基于集合的模型（SBM）的扩展，它是一种有效的技术，用于基于同现模式来计算术语权重，用于处理连词和短语查询。考虑到直觉上与语义相关的术语出现经常彼此靠近的想法。新颖之处在于，所有解决共现模式的已知方法最初都是设计用于处理析取（OR）查询的，而我们的扩展提供了一种简单，有效和高效的方式来处理析取（AND）和短语查询。该技术省时，但在检索效率方面却有不错的提高。实验结果表明，我们的扩展提高了所有评估集合的答案集的平均精度，从而使计算成本降低了。对于TReC-8集合，我们的扩展使针对连词和短语查询的平均精度曲线相对于标准向量空间模型分别提高了23.32％和18.98％。

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