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A Temporal Data Mining Approach for Discovering Knowledge on the Changes of the Patient’s Physiology

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A novel biclustering algorithm for the discovery of meaningful biological correlations between microRNAs and their target genes

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An Unsupervised Framework for Topological Relations Extraction from Geographic Documents

Collective Inference for Handling Autocorrelation in Network Regression

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Computational annotation of UTR cis-regulatory modules through Frequent Pattern Mining

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Discovering Evolution Chains in Dynamic Networks

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Document Image Understanding through Iterative Transductive Learning

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Mining Dense Regions from Vehicular Mobility in Streaming Setting

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Mining Multiple Level Non-redundant Association Rules through Two-Fold Pruning of Redundancies

Mining Spatial Association Rules for Composite Motif Discovery

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Novelty Detection from Evolving Complex Data Streams with Time Windows

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Relational Frequent Patterns Mining for Novelty Detection from Data Streams

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Relational mining for discovering changes in evolving networks

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