Understanding Search Engines : Mathematical Modeling and Text Retrieval (Software, Environments, Tools)

Understanding Search Engines discusses many of the key design issues for building search engines and emphasizes the important roles that applied mathematics can play in improving information retrieval. The authors discuss not only important data structures, algorithms, and software but also user-centered issues such as interfaces, manual indexing, and document preparation.

The authors bridge the gap between applied mathematics and information retrieval. They discuss some of the current problems in information retrieval that may not be familiar to applied mathematicians and computer scientists and present some of the driving computational methods (SVD, SDD) for automated conceptual indexing.

This book uses a new approach to the subject by introducing topics in a nontechnical way and provides insights into common problems found in information retrieval. The more mathematical details are offset from the regular text.

Michael W. Berry is Associate Professor of Computer Science at the University of Tennessee. He is a member of SIAM, ACM, and the IEEE Computer Society. He is coauthor of Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods (SIAM, 1993). Murray Browne is a Research Associate in the Department of Computer Science at the University of Tennessee. He is a member of ASIS and has published numerous essays, book reviews, and feature stories.