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Elegant Arm Using Parallel by Verma Gurudatta (4 results)
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Elegant ARM Using Parallel Processing | An Approach Towards Multi-Core Programming
Language: English
Published by LAP Lambert Academic Publishing, 2012
ISBN 10: 3659273783 ISBN 13: 9783659273780
Taschenbuch. Condition: Neu. Elegant ARM Using Parallel Processing | An Approach Towards Multi-Core Programming | Gurudatta Verma | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659273780 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Elegant ARM Using Parallel Processing: An Approach Towards Multi-Core Programming
Language: English
Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659273783 ISBN 13: 9783659273780
Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Elegant ARM Using Parallel Processing
Language: English
Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659273783 ISBN 13: 9783659273780
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Verma GurudattaGurudatta Verma is a faculty in Deptt. of Computer Science RSRRCET,Bhilai.He acquired BE(IT) from RCET,Bhilai affiliated to Pt.RSSU, Raipur. He is currently pursuing M.Tech in Computer Science & Engineering from CSIT, .
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Elegant ARM Using Parallel Processing : An Approach Towards Multi-Core Programming
Language: English
Published by LAP Lambert Academic Publishing, 2012
ISBN 10: 3659273783 ISBN 13: 9783659273780
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Association mining is one of the most researched areas of data mining and has received much attention from the database community. Association rules are interesting correlations among attributes in a database. These rules have many applications in areas ranging from e-commerce to sports to census analysis to medical diagnosis. The most time consuming operation in discovery of association rules is computation of frequency of interesting subset of items (called candidates) in the database of transactions. Hence, it has become vital to develop a method that may avoid or reduce candidate generation and test, utilize some novel data structures to reduce the cost in frequent pattern mining. An Effectual Generalized Mesh Transposition Algorithm (EGMTA) is proposed which is an integrated approach of Parallel Computing and ARM for mining Association Rules in Generalized data set. EGMTA is fundamentally different from all the previous algorithms. As EGMTA uses database in transposed form which has been done using Parallel transposition (Mesh Transpose), hence to generate all significant association rules number of passes required is reduced.
