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Passage Retrieval in Log Files: An Approach Based on Query Enrichment

机译:日志文件中的段落检索:一种基于查询富集的方法

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The question answering systems are considered the next generation of search engines. This paper focuses on the first step of this process, which is to search for relevant passages containing answers. Passage Retrieval, can be difficult because of the complexity of data, log files in our case. Our contribution is based on the enrichment of queries by using a learning method and a novel term weighting function. This original term weighting function, used within the enrichment process, aims to assign a weight to terms according to their relatedness to the context of answers. Experiments conducted on real data show that our protocol of primitive query enrichment make it possible to retrieve relevant passages.
机译:问题应答系统被认为是下一代搜索引擎。本文重点介绍该过程的第一步,即寻找包含答案的相关段落。通过检索,由于数据的复杂性,在我们的情况下可能是困难的。我们的贡献是基于使用学习方法和新型术语加权函数来富集查询。这种原始的术语加权函数在浓缩过程中使用,旨在根据其相关性对答案的相关性分配权重。在实际数据上进行的实验表明,我们的原始查询富集协议使得可以检索相关段落。

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