
Similarity Search
The Metric Space Approach
Springer (Publisher)
Published on 23. November 2010
Book
Paperback/Softback
XVII, 220 pages
978-1-4419-3972-2 (ISBN)
Description
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.
More details
Series
Edition
1st ed. Softcover of orig. ed. 2006
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Professional/practitioner
Illustrations
XVII, 220 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 14 mm
Weight
371 gr
ISBN-13
978-1-4419-3972-2 (9781441939722)
DOI
10.1007/0-387-29151-2
Schweitzer Classification
Other editions
Additional editions

Book
11/2005
Springer
€106.99
Shipment within 5-7 days
Content
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.