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Titlebook: Knowledge Discovery in Inductive Databases; Third International Bart Goethals,Arno Siebes Conference proceedings 2005 Springer-Verlag Berl

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Database Transposition for Constrained (Closed) Pattern Miningaint transposition and look into classical constraints. We then address the problem of generating the closed patterns of the original database satisfying the constraint, starting from those mined in the “transposed” database. Finally, we show how to generate all the patterns satisfying the constraint from the closed ones.
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An Automata Approach to Pattern Collectionstion supports visualization of the patterns in the collection and clustering of the patterns based on their structural properties and interestingness values. Furthermore, we show experimentally that finite automata provide a space-efficient way to represent itemset collections.
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Knowledge Discovery in Inductive Databases978-3-540-31841-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
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https://doi.org/10.1007/b106731Pattern Mining; algorithms; association rules; data integration; data mining; data models; data patterns; f
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/k/image/543876.jpg
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2366-2557 leading experts across the globe.Covers advances in the fiel.This book comprises the proceedings of the Sixth International Conference of Transportation Research Group of India (CTRG2021) focusing on emerging opportunities and challenges in the field of transportation of people and freight. The cont
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