Pavel Zezula, Giuseppe Amato, Vlastislav Dohnal, Michal Batko

Similarity Search (eBook, PDF)

The Metric Space Approach

• Format: PDF

Produktbeschreibung

In the Information Society, information holds the master key to economic influence. Similarity Search: The Metric Space Approach will focus on efficient ways to locate user-relevant information in collections of objects, the similarity of which is quantified using a pairwise distance measure. This book is a direct response to recent advances in computing, communications and storage which have led to the current flood of digital libraries, data warehouses and the limitless heterogeneity of internet resources.

Similarity Search: The Metric Space Approach will introduce state-of-the-art in developing index structures for searching complex data modeled as instances of a metric space. This book consists of two parts. Part 1 presents the metric search approach in a nutshell by defining the problem, describes major theoretical principals, and provides an extensive survey of specific techniques for a large range of applications. Part 2 concentrates on approaches particularly designed for searching in very large collections of data.

Similarity Search: The Metric Space Approach is designed for a professional audience, composed of academic researchers as well as practitioners in industry. This book is also suitable as introductory material for graduate-level students in computer science.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 220
• Erscheinungstermin: 7. Juni 2006
• Englisch
• ISBN-13: 9780387291512
• Artikelnr.: 37286979

Autorenporträt

Pavel Zezula, Masaryk University, Brno, Czech Republic / Giuseppe Amato, ISTI-CNR, Pisa, Italy / Vlastislav Dohnal, Masaryk University, Brno, Czech Republic / Michal Batko, Masaryk University, Brno, Czech Republic

Inhaltsangabe

Metric Searching in a Nutshell.- Foundations of Metric Space Searching.- Survey of Existing Approaches.- Metric Searching in Large Collections of Data.- Centralized Index Structures.- Approximate Similarity Search.- Parallel and Distributed Indexes.