David A. Grossman, Ophir Frieder

Information Retrieval (eBook, PDF)

Algorithms and Heuristics

• Format: PDF

Produktbeschreibung

Information Retrieval: Algorithms and Heuristics is a comprehensive introduction to the study of information retrieval covering both effectiveness and run-time performance. The focus of the presentation is on algorithms and heuristics used to find documents relevant to the user request and to find them fast. Through multiple examples, the most commonly used algorithms and heuristics needed are tackled. To facilitate understanding and applications, introductions to and discussions of computational linguistics, natural language processing, probability theory and library and computer science are provided. While this text focuses on algorithms and not on commercial product per se, the basic strategies used by many commercial products are described. Techniques that can be used to find information on the Web, as well as in other large information collections, are included. This volume is an invaluable resource for researchers, practitioners, and students working in information retrieval and databases. For instructors, a set of Powerpoint slides, including speaker notes, are available online from the authors.

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Produktdetails

• Verlag: Springer New York
• Seitenzahl: 254
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461555391
• Artikelnr.: 43991950

Inhaltsangabe

1. Introduction.- 2. Retrieval Strategies.- 2.1 Vector Space Model.- 2.2 Probabilistic Retrieval Strategies.- 2.3 Language Models.- 2.4 Inference Networks.- 2.5 Extended Boolean Retrieval.- 2.6 Latent Semantic Indexing.- 2.7 Neural Networks.- 2.8 Genetic Algorithms.- 2.9 Fuzzy Set Retrieval.- 2.10 Summary.- 2.11 Exercises.- 3. Retrieval Utilities.- 3.1 Relevance Feedback.- 3.2 Clustering.- 3.3 Passage-based Retrieval.- 3.4 N-grams.- 3.5 Regression Analysis.- 3.6 Thesauri.- 3.7 Semantic Networks.- 3.8 Parsing.- 3.9 Summary.- 3.10 Exercises.- 4. Cross-Language Information Retrieval.- 4.1 Introduction.- 4.2 Crossing the Language Barrier.- 4.3 Cross-Language Retrieval Strategies.- 4.4 Cross Language Utilities.- 4.5 Summary.- 4.6 Exercises.- 5. Efficiency.- 5.1 Inverted Index.- 5.2 Query Processing.- 5.3 Signature Files.- 5.4 Duplicate Document Detection.- 5.5 Summary.- 5.6 Exercises.- 6. Integrating Structured Data and Text.- 6.1 Review of the Relational Model.- 6.2 A Historical Progression.- 6.3 Information Retrieval as a Relational Application.- 6.4 Semi-Structured Search using a Relational Schema.- 6.5 Multi-dimensional Data Model.- 6.6 Mediators.- 6.7 Summary.- 6.8 Exercises.- 7. Parallel Information Retrieval.- 7.1 Parallel Text Scanning.- 7.2 Parallel Indexing.- 7.3 Clustering and Classification.- 7.4 Large Parallel Systems.- 7.5 Summary.- 7.6 Exercises.- 8. Distributed Information Retrieval.- 8.1 A Theoretical Model of Distributed Retrieval.- 8.2 Web Search.- 8.3 Result Fusion.- 8.4 Peer-to-Peer Information Systems.- 8.5 Other Architectures.- 8.6 Summary.- 8.7 Exercises.- 9. Summary and Future Directions.- References.