| Class-tested and coherent, this groundbreaking new textbook teaches web-era information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. Written from a computer science perspective by three leading experts in the field, it gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Although originally designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also create a buzz for researchers and professionals alike.
Coherent and up -to -date, this textbook for advanced undergraduate and beginning graduate students in computer science covers all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections
About the Author
Christopher Manning is an Associate Professor of Computer Science and Linguistics at Stanford University. His research concentrates on probabilistic models of language and statistical natural language processing, information extraction, text understanding and text mining.
Dr Prabhakar Raghavan is Head of Yahoo! Research and a Consulting Professor of Computer Science at Stanford University.
Dr Hinrich Schütze resides as Chair of Theoretical Computational Linguistics at the Institute for Natural Language Processing, University of Stuttgart, |
