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Titlebook: New Frontiers in Mining Complex Patterns; Second International Annalisa Appice,Michelangelo Ceci,Zbigniew W. Ras Conference proceedings 201

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Trajectory Data Pattern Mininggs. We mine frequent trajectories using a sliding windows approach combined with a counting algorithm that allows us to promptly update the frequency of patterns. In order to make counting really efficient, we represent frequent trajectories by prime numbers, whereby the Chinese reminder theorem can then be used to expedite the computation.
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0302-9743 nd time series analysis, classification, clustering and pattern discovery, graphs, networks and relational data, machine learning and music data.978-3-319-08406-0978-3-319-08407-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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A Hybrid Distance-Based Method and Support Vector Machines for Emotional Speech Detectionable for speech signal, it can also be used to analyse other data of similar nature. The proposed method is tested using four emotional databases. Results showed competitive performance yielding an average accuracy of at least 80 % on three databases for the detection of basic types of emotion.
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Methods for the Efficient Discovery of Large Item-Indexable Sequential Patternser item-indexable databases with heightened efficiency. Second, we propose a pattern-merging procedure, MergeIndexBic, to efficiently discover lengthy noise-tolerant sequential patterns. The superior performance of IndexSpan and MergeIndexBic against competitive alternatives is demonstrated on both
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