Introduction to Information Retrieval

ISBN-10: 0521865719

ISBN-13: 9780521865715

Edition: 2008

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Description: Introduction to Information Retrieval is the first textbook with a coherent treatment of classical and web information retrieval, including web search and the related areas of text classification and text clustering. Written from a computer science perspective, 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. Designed as the primary text for a graduate or advanced undergraduate course in information retrieval, the book will also interest researchers and professionals. A complete set of lecture slides and exercises that accompany the book are available on the web.

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Book details

List price: $69.00
Copyright year: 2008
Publisher: Cambridge University Press
Publication date: 7/7/2008
Binding: Hardcover
Pages: 496
Size: 7.00" wide x 10.00" long x 1.00" tall
Weight: 2.288
Language: English

Table of Notation
Preface
Boolean retrieval
An example information retrieval problem
A first take at building an inverted index
Processing Boolean queries
The extended Boolean model versus ranked retrieval
References and further reading
The term vocabulary and postings lists
Document delineation and character sequence decoding
Determining the vocabulary of terms
Faster postings list intersection via skip pointers
Positional postings and phrase queries
References and further reading
Dictionaries and tolerant retrieval
Search structures for dictionaries
Wildcard queries
Spelling correction
Phonetic correction
References and further reading
Index construction
Hardware basics
Blocked sort-based indexing
Single-pass in-memory indexing
Distributed indexing
Dynamic indexing
Other types of indexes
References and further reading
Index compression
Statistical properties of terms in information retrieval
Dictionary compression
Postings file compression
References and further reading
Scoring, term weighting, and the vector space model
Parametric and zone indexes
Term frequency and weighting
The vector space model for scoring
Variant tf-idf functions
References and further reading
Computing scores in a complete search system
Efficient scoring and ranking
Components of an information retrieval system
Vector space scoring and query operator interaction
References and further reading
Evaluation in information retrieval
Information retrieval system evaluation
Standard test collections
Evaluation of unranked retrieval sets
Evaluation of ranked retrieval results
Assessing relevance
A broader perspective: System quality and user utility
Results snippets
References and further reading
Relevance feedback and query expansion
Relevance feedback and pseudo relevance feedback
Global methods for query reformulation
References and further reading
XML retrieval
Basic XML concepts
Challenges in XML retrieval
A vector space model for XML retrieval
Evaluation of XML retrieval
Text-centric versus data-centric XML retrieval
References and further reading
Probabilistic information retrieval
Review of basic probability theory
The probability ranking principle
The binary independence model
An appraisal and some extensions
References and further reading
Language models for information retrieval
Language models
The query likelihood model
Language modeling versus other approaches in information retrieval
Extended language modeling approaches
References and further reading
Text classification and Naive Bayes
The text classification problem
Naive Bayes text classification
The Bernoulli model
Properties of Naive Bayes
Feature selection
Evaluation of text classification
References and further reading
Vector space classification
Document representations and measures of relatedness in vector spaces
Rocchio classification
k nearest neighbor
Linear versus nonlinear classifiers
Classification with more than two classes
The bias-variance tradeoff
References and further reading
Support vector machines and machine learning on documents
Support vector machines: The linearly separable case
Extensions to the support vector machine model
Issues in the classification of text documents
Machine-learning methods in ad hoc information retrieval
References and further reading
Flat clustering
Clustering in information retrieval
Problem statement
Evaluation of clustering
K-means
Model-based clustering
References and further reading
Hierarchical clustering
Hierarchical agglomerative clustering
Single-link and complete-link clustering
Group-average agglomerative clustering
Centroid clustering
Optimality of hierarchical agglomerative clustering
Divisive clustering
Cluster labeling
Implementation notes
References and further reading
Matrix decompositions and latent semantic indexing
Linear algebra review
Term-document matrices and singular value decompositions
Low-rank approximations
Latent semantic indexing
References and further reading
Web search basics
Background and history
Web characteristics
Advertising as the economic model
The search user experience
Index size and estimation
Near-duplicates and shingling
References and further reading
Web crawling and indexes
Overview
Crawling
Distributing indexes
Connectivity servers
References and further reading
Link analysis
The Web as a graph
PageRank
Hubs and authorities
References and further reading
Bibliography
Index
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