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1. k-STARs: Sequences of Spatio-Temporal Association Rules

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2. Sinks, Stationary Regions and Thoroughfares in Object Mobility Databases

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3. Using significant, positively associated and relatively class correlated rules for association classification of imbalanced datasets

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4. Mining Complex, Maximal and Complete Sub-graphs and Sets of Correlated Variables with Applications to Feature Subset Selection

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5. Using significant positively associated and relatively class correlated rules for associative classification of imbalanced datasets

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6. Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases

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7. Geometrically Inspired Itemset Mining

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8. Geometrically Inspired Itemset Mining

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9. Mining complex spatio-temporal sequence patterns

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10. Mining spatio-temporal association rules, sources, sinks, stationary regions and thoroughfares in object mobility databases

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