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Record Nr. |
UNINA9910299254003321 |
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Autore |
P Deepak |
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Titolo |
Operators for Similarity Search : Semantics, Techniques and Usage Scenarios / / by Deepak P, Prasad M. Deshpande |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (122 p.) |
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Collana |
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SpringerBriefs in Computer Science, , 2191-5768 |
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Disciplina |
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Soggetti |
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Information 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 |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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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. |
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Sommario/riassunto |
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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 |
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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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