Pattern extraction is one of the major topics in the Knowledge Discovery from Data & Background Knowledge Integration research domains. Extensively, it is subsumed as a part of the data mining task. Out of numerous data mining techniques, association rule mining and bi-clustering are two major complementary data mining tasks for relevant knowledge extraction and integration. However, to the best of our knowledge, no approach was proposed to perform these two tasks in one process. In this book, we shown an original approach for extracting different categories of knowledge patterns while using minimum number of resources. They extend the classical frameworks of association rules & bi-clusters, by providing the user with more information using the object lists associated with these patterns. These patterns are generated from the sets of generators, or key-patterns, the sets of closed patterns and the hierarchical conceptual structure induced from generators, closed patterns and supporting object lists. This book focuses on these topics in details.
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Kartick Chandra Mondal is an Assistant Prof. in the Dept. of Information Tech. at Jadavpur University, India. His research interests are Data Mining, Bioinformatics, Biodiversity & Cloud Computing. He has completed his PhD from University of Nice Sophia Antipolis, France & served as PostDoc Researcher for 1 year in University of Strasbourg, France.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Pattern extraction is one of the major topics in the Knowledge Discovery from Data & Background Knowledge Integration research domains. Extensively, it is subsumed as a part of the data mining task. Out of numerous data mining techniques, association rule mining and bi-clustering are two major complementary data mining tasks for relevant knowledge extraction and integration. However, to the best of our knowledge, no approach was proposed to perform these two tasks in one process. In this book, we shown an original approach for extracting different categories of knowledge patterns while using minimum number of resources. They extend the classical frameworks of association rules & bi-clusters, by providing the user with more information using the object lists associated with these patterns. These patterns are generated from the sets of generators, or key-patterns, the sets of closed patterns and the hierarchical conceptual structure induced from generators, closed patterns and supporting object lists. This book focuses on these topics in details. 336 pp. Englisch. Bestandsnummer des Verkäufers 9783330045552
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Mondal Kartick ChandraKartick Chandra Mondal is an Assistant Prof. in the Dept. of Information Tech. at Jadavpur University, India. His research interests are Data Mining, Bioinformatics, Biodiversity & Cloud Computing. He has comple. Bestandsnummer des Verkäufers 385707617
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Taschenbuch. Zustand: Neu. Algorithms for Data Mining and Bio-informatics | Kartick Chandra Mondal (u. a.) | Taschenbuch | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9783330045552 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 118669478
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Pattern extraction is one of the major topics in the Knowledge Discovery from Data & Background Knowledge Integration research domains. Extensively, it is subsumed as a part of the data mining task. Out of numerous data mining techniques, association rule mining and bi-clustering are two major complementary data mining tasks for relevant knowledge extraction and integration. However, to the best of our knowledge, no approach was proposed to perform these two tasks in one process. In this book, we shown an original approach for extracting different categories of knowledge patterns while using minimum number of resources. They extend the classical frameworks of association rules & bi-clusters, by providing the user with more information using the object lists associated with these patterns. These patterns are generated from the sets of generators, or key-patterns, the sets of closed patterns and the hierarchical conceptual structure induced from generators, closed patterns and supporting object lists. This book focuses on these topics in details.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 336 pp. Englisch. Bestandsnummer des Verkäufers 9783330045552
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Pattern extraction is one of the major topics in the Knowledge Discovery from Data & Background Knowledge Integration research domains. Extensively, it is subsumed as a part of the data mining task. Out of numerous data mining techniques, association rule mining and bi-clustering are two major complementary data mining tasks for relevant knowledge extraction and integration. However, to the best of our knowledge, no approach was proposed to perform these two tasks in one process. In this book, we shown an original approach for extracting different categories of knowledge patterns while using minimum number of resources. They extend the classical frameworks of association rules & bi-clusters, by providing the user with more information using the object lists associated with these patterns. These patterns are generated from the sets of generators, or key-patterns, the sets of closed patterns and the hierarchical conceptual structure induced from generators, closed patterns and supporting object lists. This book focuses on these topics in details. Bestandsnummer des Verkäufers 9783330045552
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