Algorithms for Data Mining and Bio-informatics
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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 m...
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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