04239nam 22007215 450 991029925400332120200703113747.03-319-21257-510.1007/978-3-319-21257-9(CKB)3710000000444412(EBL)3567613(SSID)ssj0001534802(PQKBManifestationID)11995418(PQKBTitleCode)TC0001534802(PQKBWorkID)11498120(PQKB)10056538(DE-He213)978-3-319-21257-9(MiAaPQ)EBC3567613(PPN)187686335(EXLCZ)99371000000044441220150707d2015 u| 0engur|n|---|||||txtccrOperators for Similarity Search Semantics, Techniques and Usage Scenarios /by Deepak P, Prasad M. Deshpande1st ed. 2015.Cham :Springer International Publishing :Imprint: Springer,2015.1 online resource (122 p.)SpringerBriefs in Computer Science,2191-5768Description based upon print version of record.3-319-21256-7 Includes bibliographical references at the end of each chapters and index.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.SpringerBriefs in Computer Science,2191-5768Information storage and retrievalComputer science—MathematicsArtificial intelligenceData miningInformation Storage and Retrievalhttps://scigraph.springernature.com/ontologies/product-market-codes/I18032Discrete Mathematics in Computer Sciencehttps://scigraph.springernature.com/ontologies/product-market-codes/I17028Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Data Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Information storage and retrieval.Computer science—Mathematics.Artificial intelligence.Data mining.Information Storage and Retrieval.Discrete Mathematics in Computer Science.Artificial Intelligence.Data Mining and Knowledge Discovery.006.312P Deepakauthttp://id.loc.gov/vocabulary/relators/aut1060962Deshpande Prasad Mauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910299254003321Operators for Similarity Search2516485UNINA