Details
Similarity Search
The Metric Space ApproachAdvances in Database Systems, Band 32
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96,29 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 07.06.2006 |
| ISBN/EAN: | 9780387291512 |
| Sprache: | englisch |
| Anzahl Seiten: | 220 |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
The area of similarity searching is a very hot topic for both research and c- mercial applications. Current data processing applications use data with c- siderably less structure and much less precise queries than traditional database systems. Examples are multimedia data like images or videos that offer query by example search, product catalogs that provide users with preference based search, scientific data records from observations or experimental analyses such as biochemical and medical data, or XML documents that come from hetero- neous data sources on the Web or in intranets and thus does not exhibit a global schema. Such data can neither be ordered in a canonical manner nor meani- fully searched by precise database queries that would return exact matches. This novel situation is what has given rise to similarity searching, also - ferred to as content based or similarity retrieval. The most general approach to similarity search, still allowing construction of index structures, is modeled in metric space. In this book. Prof. Zezula and his co authors provide the first monograph on this topic, describing its theoretical background as well as the practical search tools of this innovative technology.
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.
<P>In the Information Society, information holds the master key to economic influence. <STRONG>Similarity Search: The Metric Space Approach</STRONG> 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. </P>
<P><STRONG>Similarity Search: The Metric Space Approach</STRONG> 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.</P>
<P><STRONG>Similarity Search: The Metric Space Approach</STRONG> 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. </P>
<P><STRONG>Similarity Search: The Metric Space Approach</STRONG> 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.</P>
<P><STRONG>Similarity Search: The Metric Space Approach</STRONG> 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. </P>
Contains extensive survey, and considers index structures ranging from main memory based to scalable and distributed implementations exploiting parallelism Comprehensive and detailed presentation of theory, techniques and their implementations, as well as reported results from experimental trials Applications areas include the retrieval of text, images, CAD objects, videos and proteins Includes supplementary material: sn.pub/extras
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