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Mining Maximal Generalized Frequent Geographic ...
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由 V Bogorny 著作2006被引用 31 次 — This paper presents a novel approach for mining frequent geographic patterns without associations that are previously known as non- interesting. Geographic ...
Mining Maximal Generalized Frequent Geographic Patterns with ...
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In frequent geographic pattern mining a large amount of patterns is well known a priori. This paper presents a novel approach for mining frequent geographic ...
Mining Maximal Generalized Frequent Geographic Patterns with ...
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This paper presents a novel approach for mining spatial association rules, using background knowledge, using the use of geographic database schemas and ...
(PDF) Mining Maximal Generalized Frequent Geographic ...
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This paper presents a novel approach for mining frequent geographic patterns without associations that are previously known as noninteresting. Geographic ...
Mining Maximal Generalized Frequent Geographic Patterns with ...
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This paper presents a novel approach for mining frequent geographic patterns without associations that are previously known as non-interesting. Geographic ...
Mining Maximal Generalized Frequent Geographic Patterns with ...
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Bogorny V. et al. Mining Maximal Generalized Frequent Geographic Patterns with Knowledge Constraints // Sixth International Conference on Data Mining (ICDM'06).
Mining Maximal Generalized Frequent Geographic Patterns
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Mining MGFGP with Knowledge Constraint 5. Conclusions and Future Work First approach used is quantitative reasoning that calculate the distance relationship on ...
Mining Maximal Generalized Frequent Geographic Patterns ... - dblp
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Bibliographic details on Mining Maximal Generalized Frequent Geographic Patterns with Knowledge Constraints.
(PDF) Mining frequent geographic patterns with knowledge ...
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2006年11月10日 — This paper presents a two step method for mining frequent geographic patterns without associations that are previously known as non-interesting.
Sandro da Silva Camargo
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Mining maximal generalized frequent geographic patterns with knowledge constraints. V Bogorny, J Valiati, S Camargo, P Engel, B Kuijpers, LO Alvares. Sixth ...