Titlebook: A Feature-Centric View of Information Retrieval; Donald Metzler Book 2011 Springer-Verlag Berlin Heidelberg 2011 Markov models.Web queries

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Feature-Based Query Expansion,tion ‘immigrant’ who held dual Dutch-Moroccan nationality and was convicted of the murder in 2005, had spent his whole life in the Netherlands and yet, according to his confession to the murder, renounced the culture of Dutch society and its democracy. Whether or not failures of integration had anyt

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Aid and Power in the Arab Worldls that go beyond the bag of words assumption. The bag of words models covered include the binary independence retrieval model, the 2-Poisson model, the BM25 model, unigram language models, and several other bag of words models. The models covered that go beyond the bag of words assumption include n

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https://doi.org/10.1057/9781137023483CE). The approach has three key benefits, including the ability to go beyond the bag of words assumption, the ability to employ arbitrary features during the query expansion process, and the ability to expand with a variety of concept types beyond unigrams. In addition to the basic LCE model, the ch

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Aid for Trade for Sustainable Developmentthe importance of query term concepts in a way that directly optimizes an underlying retrieval metric. By implementing concept weighting directly into the underlying retrieval model it avoids the issue of metric divergence. The chapter concludes with a rigorous experimental evaluation that demonstra

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Philippe De Lombaerde,George Mavrotasdescribing a number of techniques to estimate the model parameters in such a way that the resulting ranking functions are optimized for a target retrieval metric. The section describes a number of numerical analysis-based approaches, as well as a number of more sophisticated machine learning-inspire

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A Feature-Centric View of Information Retrieval978-3-642-22898-8Series ISSN 1871-7500 Series E-ISSN 2730-6836

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https://doi.org/10.1007/978-3-642-22898-8Markov models; Web queries; information retrieval; learning to rank; model mearing; search engines; “Bag o