This book aims at providing a thorough and updated introduction to the key Information Retrieval (IR) concepts and technologies behind search engines. In the modern online world, seeking and finding information of value is of paramount importance and, for this, people often refer to search engines because of their inherent effectiveness and simplicity. Search engines work because they are anchored on the field of IR – the primary goal of an IR system is to retrieve all the documents that are relevant to a user information query, while retrieving as few non-relevant documents as possible. This ambitious view of the problem naturally leads to a wealth of concepts and technologies, which are required to implement the search box paradigm.
From parsing to indexing, clustering to classification, retrieval to ranking, and user feedback to retrieval evaluation, all of the most important concepts are carefully introduced and exemplified. The contents and structure of the book have been carefully designed by the two main authors, and the contributions of Eric Brown, Carlos Castillo, Marcos Gonçalves, David Hawking, Marti Hearst, Mounia Lalmas, Yoelle Maarek, Christian Middleton, Gonzalo Navarro, Dulce Ponceleón, Edie Rasmussen, Malcolm Slaney, and Nivio Ziviani greatly enrich the text with individual expertise from leaders in the field.
This completely reorganized, revised and enlarged second edition of Modern Information Retrieval contains four new chapters and double the number of pages and bibliographic references of the first edition, and a companion website with teaching material. It will prove invaluable to students, professors, researchers, practitioners, and scholars of this fascinating field of IR.