BOOK-CHAPTER

Relevance feedback and query expansion

Christopher D. ManningPrabhakar RaghavanHinrich Schütze

Year: 2008 Cambridge University Press eBooks Pages: 162-177   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:
Relevance feedback Relevance (law) Query expansion Computer science Information retrieval Artificial intelligence Political science

Metrics

23
Cited By
3.34
FWCI (Field Weighted Citation Impact)
0
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing
Advanced Database Systems and Queries
Physical Sciences →  Computer Science →  Computer Networks and Communications
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence

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