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A Generative Theory of Relevance

A Generative Theory of Relevance


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About the Book

Relevance.- A Generative View of Relevance.- Generative Density Allocation.- Retrieval Scenarios.- Conclusion.
About the Author:

Victor Lavrenko is a lecturer at the School of Informatics at the University of Edinburgh, Scotland, UK. He received his Ph.D. in Computer Science from the University of Massachusetts Amherst in 2004. His dissertation focused on a generative framework for modeling relevance in Information Retrieval. In 2005 he joined the Center for Intelligent Information Retrieval at UMass as a post-doctoral research associate, working on statistical models for searching large semi-structured databases. From 2006 Victor worked as a language technology consultant for the Credit Suisse Group. Since 2000, he has served as a reviewer for SIGIR, CIKM, NAACL/HLT, IJCAI and NIPS conferences.

Victor's current research interests include formal models for searching text in multiple languages, annotating and retrieving images, and detecting and tracking novel events in the news.


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Product Details
  • ISBN-13: 9783642100420
  • Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
  • Binding: Paperback
  • Height: 234 mm
  • No of Pages: 197
  • Series Title: Information Retrieval
  • Weight: 367 gr
  • ISBN-10: 3642100422
  • Publisher Date: 20 Nov 2010
  • Edition: Softcover reprint of hardcover 1st ed. 2009
  • Language: English
  • Returnable: Y
  • Spine Width: 12 mm
  • Width: 156 mm


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