Two leaders of research and development here at Catalyst have helped write a seminal new book on search and information retrieval, Next Generation Search Engines: Advanced Models for Information Retrieval, released in March by IGI Global.

Bruce Kiefer, leader of the platform group at Catalyst, and Reed Esau, a platform architect focused on research and development at Catalyst, together with Michael W. Berry, associate director of the Center for Intelligent Systems & Machine Learning at the University of Tennessee, co-authored the book’s chapter, “The Use of Text Mining Techniques in Electronic Discovery for Legal Matters.”

As volumes of e-discovery data have outgrown the manual processes long used to make relevance judgments, Kiefer and Esau explain how methods of text mining and information retrieval, including predictive coding, can be used to help reduce data volumes. Acknowledging that text-mining techniques have so far delivered uneven results, they start the chapter by looking at the historical bias of the collection process. They then examine how tools like classifiers, latent semantic analysis, and non-negative matrix factorization can deal with nuances of the collection process.

Their chapter is part of a book intended for scientists and decision-makers who wish to gain working knowledge about search in order to evaluate available options and to engage in a dialogue with software and data providers. The aim of the book is to give readers a better understanding of the latest trends in applied research.

The book is available for purchase in hardcover and e-book editions from IGI Global (www.igi-global.com). The individual chapter can be purchased separately as a PDF download.

For more information about the book and the authors, see the full announcement.