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Operators for similarity search = semantics, techniques and usage scenarios /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Operators for similarity search/ by Deepak P, Prasad M. Deshpande.
Reminder of title:	semantics, techniques and usage scenarios /
Author:	P, Deepak.
other author:	Deshpande, Prasad M.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xi, 115 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Data mining. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-21257-9
ISBN:	9783319212579 (electronic bk.)

Operators for similarity search = semantics, techniques and usage scenarios /
P, Deepak.

Operators for similarity searchsemantics, techniques and usage scenarios /[electronic resource] :by Deepak P, Prasad M. Deshpande. - Cham :Springer International Publishing :2015. - xi, 115 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - SpringerBriefs in computer science..

1 Introduction -- 2 Fundamentals of Similarity Search -- 3 Common Similarity Search Operators -- 4 Categorizing Operators -- 5 Advanced Operators for Similarity Search -- 6 Indexing for Similarity Search Operators -- 7 The Road Ahead.

This book provides a comprehensive tutorial on similarity operators. The authors systematically survey the set of similarity operators, primarily focusing on their semantics, while also touching upon mechanisms for processing them effectively. The book starts off by providing introductory material on similarity search systems, highlighting the central role of similarity operators in such systems. This is followed by a systematic categorized overview of the variety of similarity operators that have been proposed in literature over the last two decades, including advanced operators such as RkNN, Reverse k-Ranks, Skyline k-Groups and K-N-Match. Since indexing is a core technology in the practical implementation of similarity operators, various indexing mechanisms are summarized. Finally, current research challenges are outlined, so as to enable interested readers to identify potential directions for future investigations. In summary, this book offers a comprehensive overview of the field of similarity search operators, allowing readers to understand the area of similarity operators as it stands today, and in addition providing them with the background needed to understand recent novel approaches.

ISBN: 9783319212579 (electronic bk.)

Standard No.: 10.1007/978-3-319-21257-9doiSubjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 005.741

Operators for similarity search = semantics, techniques and usage scenarios /
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245 1 0 $a Operators for similarity search $h [electronic resource] : $b semantics, techniques and usage scenarios / $c by Deepak P, Prasad M. Deshpande.
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505 0 $a 1 Introduction -- 2 Fundamentals of Similarity Search -- 3 Common Similarity Search Operators -- 4 Categorizing Operators -- 5 Advanced Operators for Similarity Search -- 6 Indexing for Similarity Search Operators -- 7 The Road Ahead.
520 $a This book provides a comprehensive tutorial on similarity operators. The authors systematically survey the set of similarity operators, primarily focusing on their semantics, while also touching upon mechanisms for processing them effectively. The book starts off by providing introductory material on similarity search systems, highlighting the central role of similarity operators in such systems. This is followed by a systematic categorized overview of the variety of similarity operators that have been proposed in literature over the last two decades, including advanced operators such as RkNN, Reverse k-Ranks, Skyline k-Groups and K-N-Match. Since indexing is a core technology in the practical implementation of similarity operators, various indexing mechanisms are summarized. Finally, current research challenges are outlined, so as to enable interested readers to identify potential directions for future investigations. In summary, this book offers a comprehensive overview of the field of similarity search operators, allowing readers to understand the area of similarity operators as it stands today, and in addition providing them with the background needed to understand recent novel approaches.
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