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Mining high utility item sets from a transactional database refers to the discovery of item sets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate item sets for high utility item sets. Such a large number of candidate item sets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility item sets.In this Book , we propose algorithm namely Improved mining algorithm (Utility Pattern Growth plus) for mining high utility item sets with a set of effective strategies for pruning candidate item sets. The information of high utility item sets is maintained in a tree-based data structure named UP-Tree (Utility Pattern Tree) such that candidate item sets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP Growth+ is compared with the state-of-the-art algorithms on many types of both real and synthetic datasets.
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La profesora Monali Deshmukh completó sus estudios de postgrado en la Universidad de Mumbai en computación y tiene más de 10 años de experiencia como..,Profesor asistente en SCOE, Kharghar.Es autora y coautora de muchas publicaciones científicas (revistas y conferencias). Sus intereses actuales de investigación se centran en las áreas de minería de datos y computación en nube.
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Data Mining Technique and Applications
Verlag:
LAP LAMBERT Academic Publishing Nov 2020, 2020
ISBN 10: 6203028614
ISBN 13: 9786203028614
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Mining high utility item sets from a transactional database refers to the discovery of item sets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate item sets for high utility item sets. Such a large number of candidate item sets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility item sets.In this Book , we propose algorithm namely Improved mining algorithm (Utility Pattern Growth plus) for mining high utility item sets with a set of effective strategies for pruning candidate item sets. The information of high utility item sets is maintained in a tree-based data structure named UP-Tree (Utility Pattern Tree) such that candidate item sets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP Growth+ is compared with the state-of-the-art algorithms on many types of both real and synthetic datasets. 64 pp. Englisch. Bestandsnummer des Verkäufers 9786203028614
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Data Mining Technique and Applications : Mining Method for Long Pattern from Database
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LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6203028614
ISBN 13: 9786203028614
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Mining high utility item sets from a transactional database refers to the discovery of item sets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate item sets for high utility item sets. Such a large number of candidate item sets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility item sets.In this Book , we propose algorithm namely Improved mining algorithm (Utility Pattern Growth plus) for mining high utility item sets with a set of effective strategies for pruning candidate item sets. The information of high utility item sets is maintained in a tree-based data structure named UP-Tree (Utility Pattern Tree) such that candidate item sets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP Growth+ is compared with the state-of-the-art algorithms on many types of both real and synthetic datasets. Bestandsnummer des Verkäufers 9786203028614
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Data Mining Technique and Applications
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ISBN 13: 9786203028614
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Vasantarao Deshmukh MonaliProf. Monali Deshmukh completed her graduate studies from Mumbai university in computer science engg. and having more than 10 year experience as, Asst. Professor in SCOE, Kharghar. She authored/co-authored f. Bestandsnummer des Verkäufers 452571121
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Data Mining Technique and Applications
Verlag:
LAP LAMBERT Academic Publishing Nov 2020, 2020
ISBN 10: 6203028614
ISBN 13: 9786203028614
Neu
Taschenbuch
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Mining high utility item sets from a transactional database refers to the discovery of item sets with high utility like profits. Although a number of relevant algorithms have been proposed in recent years, they incur the problem of producing a large number of candidate item sets for high utility item sets. Such a large number of candidate item sets degrades the mining performance in terms of execution time and space requirement. The situation may become worse when the database contains lots of long transactions or long high utility item sets.In this Book , we propose algorithm namely Improved mining algorithm (Utility Pattern Growth plus) for mining high utility item sets with a set of effective strategies for pruning candidate item sets. The information of high utility item sets is maintained in a tree-based data structure named UP-Tree (Utility Pattern Tree) such that candidate item sets can be generated efficiently with only two scans of database. The performance of UP-Growth and UP Growth+ is compared with the state-of-the-art algorithms on many types of both real and synthetic datasets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. Bestandsnummer des Verkäufers 9786203028614
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Data Mining Technique and Applications | Mining Method for Long Pattern from Database
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LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6203028614
ISBN 13: 9786203028614
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Taschenbuch. Zustand: Neu. Data Mining Technique and Applications | Mining Method for Long Pattern from Database | Monali Vasantarao Deshmukh (u. a.) | Taschenbuch | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786203028614 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 119474716
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