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Enhancing ad-hoc relevance weighting using probability density estimation
2011
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information - SIGIR '11
Classical probabilistic information retrieval (IR) models, e.g. BM25, deal with document length based on a trade-off between the Verbosity hypothesis, which assumes the independence of a document's relevance of its length, and the Scope hypothesis, which assumes the opposite. Despite the effectiveness of the classical probabilistic models, the potential relationship between document length and relevance is not fully explored to improve retrieval performance. In this paper, we conduct an
doi:10.1145/2009916.2009943
dblp:conf/sigir/ZhouHH11
fatcat:tgg6j2egmvd4doyrhbukboo2ny