The proliferation of information housed in computerized domains makes it vital to find tools to search these resources efficiently and effectively. Ordinary retrieval techniques are inadequate because sorting is simply impossible. Consequently, proximity searching has become a fundamental computation task in a variety of application areas.

Similarity Search focuses on the state of the art in developing index structures for searching the metric space. Part I of the text describes major theoretical principles, and provides an extensive survey of specific techniques for a large range of applications. Part II concentrates on approaches particularly designed for searching in large collections of data. After describing the most popular centralized disk-based metric indexes, approximation techniques are presented as a way to significantly speed up search time at the cost of some imprecision in query results. Finally, the scalable and distributed metric structures are discussed.

Dedication.- Foreword.- Preface.- Acknowledgements.- Part I Metric Searching in a Nutshell: Foundations of Metric Space Searching.- Survey of Existing Approaches.- Part II Metric Searching in Large Collections of Data: Centralized Index Structures.- Approximate Similarity Search.- Parallel and Distributed Indexes.- References.- Author Index.- Index.- Abbreviations.

Computer scientists, system developers, advanced-level students engaged in digital data processing, information retrieval, multimedia data, data mining and knowledge discovery