BOOK-CHAPTER

Probabilistic information retrieval

Christopher D. ManningPrabhakar RaghavanHinrich Schütze

Year: 2008 Cambridge University Press eBooks Pages: 201-217   Publisher: Cambridge University Press

Abstract

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. 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. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Keywords:
Computer science Search engine indexing Information retrieval Class (philosophy) Cluster analysis World Wide Web Graduate students Document clustering Multimedia Artificial intelligence Psychology

Metrics

17
Cited By
0.38
FWCI (Field Weighted Citation Impact)
2
Refs
0.60
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Information Retrieval and Search Behavior
Physical Sciences →  Computer Science →  Information Systems
Algorithms and Data Compression
Physical Sciences →  Computer Science →  Artificial Intelligence
Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing

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