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

Abstract : 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.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00816291
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Hassan Saneifar, Stéphane Bonniol, Anne Laurent, Pascal Poncelet, Mathieu Roche. Passage Retrieval in Log Files: An Approach Based on Query Enrichment. NLP: Natural Language Processing, Aug 2010, Reykjavík, Iceland. pp.357-368, ⟨10.1007/978-3-642-14770-8_39⟩. ⟨lirmm-00816291⟩

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