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Message: <blockquote data-quote="fda" data-source="post: 7497043" data-attributes="member: 284906">A Generative Theory of RelevanceA modern information retrieval system must have the capability to   find, organize and present very different manifestations of information –   such as text, pictures, videos or database records – any of which may   be of relevance to the user. However, the concept of relevance, while   seemingly intuitive, is actually hard to define, and it’s even harder to   model in a formal way. Lavrenko does not attempt to bring forth a new definition of   relevance, nor provide arguments as to why any particular definition   might be theoretically superior or more complete. Instead, he takes a   widely accepted, albeit somewhat conservative definition, makes several   assumptions, and from them develops a new probabilistic model that   explicitly captures that notion of relevance. With this book, he makes   two major contributions to the field of information retrieval: first, a   new way to look at topical relevance, complementing the two dominant   models, i.e., the classical probabilistic model and the language   modeling approach, and which explicitly combines documents, queries, and   relevance in a single formalism; second, a new method for modeling   exchangeable sequences of discrete random variables which does not make   any structural assumptions about the data and which can also handle  rare  events. Thus his book is of major interest to researchers and graduate   students in information retrieval who specialize in relevance modeling,   ranking algorithms, and language modeling.<a href="http://freedownloadanything.com/ebook/details/15/_a_generative_theory_of_relevance.html" target="_blank">http://freedownloadanything.com/ebook/details/15/_a_generative_theory_of_relevance.html</a></blockquote>

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