Introduction to Information Retrieval 1st Edition by Christopher Manning, Prabhakar Raghavan, Hinrich Schütze 0521865719 9780521865715

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ISBN 10: 0521865719

ISBN 13: 9780521865715

Author: Christopher D. Manning; Prabhakar Raghavan; Hinrich Schütze

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.

Introduction to Information Retrieval 1st Table of contents:

1 Boolean retrieval

1.1 An example information retrieval problem

1.2 A first take at building an inverted index

1.3 Processing Boolean queries

1.4 The extended Boolean model versus ranked retrieval

1.5 References and further reading

2 The term vocabulary and postings lists

2.1 Document delineation and character sequence decoding

2.2 Determining the vocabulary of terms

2.3 Faster postings list intersection via skip pointers

2.4 Positional postings and phrase queries

2.5 References and further reading

3 Dictionaries and tolerant retrieval

3.1 Search structures for dictionaries

3.2 Wildcard queries

3.3 Spelling correction

3.4 Phonetic correction

3.5 References and further reading

4 Index construction

4.1 Hardware basics

4.2 Blocked sort-based indexing

4.3 Single-pass in-memory indexing

4.4 Distributed indexing

4.5 Dynamic indexing

4.6 Other types of indexes

4.7 References and further reading

5 Index compression

5.1 Statistical properties of terms in information retrieval

5.2 Dictionary compression

5.3 Postings file compression

5.4 References and further reading

6 Scoring, term weighting, and the vector space model

6.1 Parametric and zone indexes

6.2 Term frequency and weighting

6.3 The vector space model for scoring

6.4 Variant tf–idf functions

6.5 References and further reading

7 Computing scores in a complete search system

7.1 Efficient scoring and ranking

7.2 Components of an information retrieval system

7.3 Vector space scoring and query operator interaction

7.4 References and further reading

8 Evaluation in information retrieval

8.1 Information retrieval system evaluation

8.2 Standard test collections

8.3 Evaluation of unranked retrieval sets

8.4 Evaluation of ranked retrieval results

8.5 Assessing relevance

8.6 A broader perspective: System quality and user utility

8.7 Results snippets

8.8 References and further reading

9 Relevance feedback and query expansion

9.1 Relevance feedback and pseudo relevance feedback

9.2 Global methods for query reformulation

9.3 References and further reading

10 XML retrieval

10.1 Basic XML concepts

10.2 Challenges in XML retrieval

10.3 A vector space model for XML retrieval

10.4 Evaluation of XML retrieval

10.5 Text-centric versus data-centric XML retrieval

10.6 References and further reading

11 Probabilistic information retrieval

11.1 Review of basic probability theory

11.2 The probability ranking principle

11.3 The binary independence model

11.4 An appraisal and some extensions

11.5 References and further reading

12 Language models for information retrieval

12.1 Language models

12.2 The query likelihood model

12.3 Language modeling versus other approaches in information retrieval

12.4 Extended language modeling approaches

12.5 References and further reading

13 Text classification and Naive Bayes

13.1 The text classification problem

13.2 Naive Bayes text classification

13.3 The Bernoulli model

13.4 Properties of Naive Bayes

13.5 Feature selection

13.6 Evaluation of text classification

13.7 References and further reading

14 Vector space classification

14.1 Document representations and measures of relatedness in vector spaces

14.2 Rocchio classification

14.3 k nearest neighbor

14.4 Linear versus nonlinear classifiers

14.5 Classification with more than two classes

14.6 The bias–variance tradeoff

14.7 References and further reading

15 Support vector machines and machine learning on documents

15.1 Support vector machines: The linearly separable case

15.2 Extensions to the support vector machine model

15.3 Issues in the classification of text documents

15.4 Machine-learning methods in ad hoc information retrieval

15.5 References and further reading

16 Flat clustering

16.1 Clustering in information retrieval

16.2 Problem statement

16.3 Evaluation of clustering

16.4 K-means

16.5 Model-based clustering

16.6 References and further reading

17 Hierarchical clustering

17.1 Hierarchical agglomerative clustering

17.2 Single-link and complete-link clustering

17.3 Group-average agglomerative clustering

17.4 Centroid clustering

17.5 Optimality of hierarchical agglomerative clustering

17.6 Divisive clustering

17.7 Cluster labeling

17.8 Implementation notes

17.9 References and further reading

18 Matrix decompositions and latent semantic indexing

18.1 Linear algebra review

18.2 Term–document matrices and singular value decompositions

18.3 Low-rank approximations

18.4 Latent semantic indexing

18.5 References and further reading

19 Web search basics

19.1 Background and history

19.2 Web characteristics

19.3 Advertising as the economic model

19.4 The search user experience

19.5 Index size and estimation

19.6 Near-duplicates and shingling

19.7 References and further reading

20 Web crawling and indexes

20.1 Overview

20.2 Crawling

20.3 Distributing indexes

20.4 Connectivity servers

20.5 References and further reading

21 Link analysis

21.1 The Web as a graph

21.2 PageRank

21.3 Hubs and authorities

21.4 References and further reading

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