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You are here: Home ▶ Information Technology (IT) ▶ Free eBook: Introduction to Information Retrieval

Free eBook: Introduction to Information Retrieval

November 9, 2009

Free eBook: Introduction to Information Retrieval

Free book “Introduction to Information Retrieval” by Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze.

Book Description

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.

Table of Contents

  • Boolean retrieval
  • The term vocabulary & postings lists
  • Dictionaries and tolerant retrieval
  • Index construction
  • Index compression
  • Scoring, term weighting & the vector space model
  • Computing scores in a complete search system
  • Evaluation in information retrieval
  • Relevance feedback & query expansion
  • XML retrieval
  • Probabilistic information retrieval
  • Language models for information retrieval
  • Text classification & Naive Bayes
  • Vector space classification
  • Support vector machines & machine learning on documents
  • Flat clustering
  • Hierarchical clustering
  • Matrix decompositions & latent semantic indexing
  • Web search basics
  • Web crawling and indexes
  • Link analysis

Download Free PDF / Read Online

Author(s): Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze
Format(s): PDF, HTML
File size: 6.44 MB
Number of pages: 569
Link: Download or read online.

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  5. Information Theory, Inference, and Learning Algorithms
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