Modern Information Retrieval

Ricardo Baeza-Yatesreceived his Ph.D. in Computer Science from the University of Waterloo, Canada in 1989. In 1992 and 1996, he was elected president of the Chilean Computer Science Society. In 1993, he received the Organization of American States award for yound researcher in exact sciences. He has several papers in various journals and is a member of ACM, AMS, EATCS, IEEE, SCC and SIAM. He is currently a full professor at the Computer Science Department of the University of more >>

Ricardo Baeza-Yatesreceived his Ph.D. in Computer Science from the University of Waterloo, Canada in 1989. In 1992 and 1996, he was elected president of the Chilean Computer Science Society. In 1993, he received the Organization of American States award for yound researcher in exact sciences. He has several papers in various journals and is a member of ACM, AMS, EATCS, IEEE, SCC and SIAM. He is currently a full professor at the Computer Science Department of the University of Chile, Santiago.

Berthier Ribeiro-Netoreveived his Ph.D. in Computer Science from the University of California, Los Angeles in 1995. He is involved with various research projects financed by Braziliam agencies; the two main projects deal with wireless information systems and video on demand. He has chaired distinguished conferences in South America and is a member of ACM, IEEE and ASIS. He is currently an associate professor at the Computer Science Department of the Federal University of Minas Gerais in Belo Horizonte, Brazil.

Information Retrieval/Database Management

Modern Information Retrieval

Ricardo Baeza-Yates and Berthier Ribeiro-Neto


We live in the information age, where swift access to relevant information in whatever form or medium can dictate the success or failure of businesses or individuals. The timely provision of relevant information with minimal ‘noise' is critical to modern society and this is what information retrieval (IR) is all about. It is a dynamic subject, with current changes driven by the expansion of the World Wide Web, the advent of modern and inexpensive graphical user interfaces and the development of reliable and low-cost mass storage devices. Modern Information Retrieval discusses all these changes in great detail and can be used for a first course on IR as well as graduate courses on the topic.

The organization of the book, which includes a comprehensive glossary, allows the reader to either obtain a broad overview or detailed knowledge of all the key topics in modern IR. The heart of the book is the nine chapters written by Baeza-Yates and Ribeiro-Neto, two leading exponents in the field. For those wishing to delve deeper into key areas there are further state-of-the-art chapters on specialized topics, fully integrated and using the same notation and terminology, written by leading researchers:

· Parallel and Distributed IR - algorithms and architectures (Eric Brown)
· User Interfaces and Visualization - the main interface paradigms for query formation and visualization of results (Marti A. Hearst)
· Multimedia IR: Models and Languages - including MULTOS and SQL3 (Elisa Bertino, Barbara Catania and Elena Ferrari)
· Multimedia IR: Indexing and Searching - R-trees and GEMINI and QBIC (Christos Faloutsos)
· Libraries and Bibliographical Systems - online systems and public access catalogs (Edie M. Rasmussen)
· Digital Libraries - the main challenges for effective deployment (Edward A Fox and Ohm Sornil)

In addition, the book contains several chapters on

· Text IR - all the main IR models, query operations, text operations, indexing and searching (three of them co-authored with Gonzalo Navarro or Nivio Ziviani)
· The Web - challenges, measures and models, search engines, directories, query languages, metasearches and trends

Modern Information Retrieval will prove invaluable to students in Computer Science, Information Science and Library Science departments, as well as to programmers and analysts working with products related to the Web, intranets, document database systems and digital libraries.


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Information retrieval (IR) has changed considerably in recent years with the expansion o << less