Understanding Search Engines

The second edition of Understanding Search Engines: Mathematical Modeling and Text Retrieval follows the basic premise of the first edition by discussing many of the key design issues for building search engines and emphasizing the important role that applied mathematics can play in improving information retrieval. The authors discuss important data structures, algorithms, and software as well as user-centered issues such as interfaces, manual indexing, and document preparation. Significant changes bring the text up to date on current information retrieval methods: for example the addition of a new chapter on link-structure algorithms used in search engines such as Google. The chapter on user interface has been rewritten to specifically focus on search engine usability. In addition the authors have added new recommendations for further reading and expanded the bibliography, and have updated and streamlined the index to make it more reader friendly.

Michael W. Berry is a Professor and Interim Department Head in the Department of Computer Science at the University of Tennessee and a faculty member in the Graduate School in Genome Science & Technology Program at the University of Tennessee and Oak Ridge National Laboratory. His current research interests include information retrieval, data mining, scientific computing, computational science, numerical linear algebra, and parallel computation.Murray Browne is a Research Associate in the Computer Science Department at the University of Tennessee. He is a member of the American Society for Information Science and Technology and has published numerous essays, book reviews, newspaper articles, and feature stories.