Mining RDF metadata for generalized association rules
In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the over-generalization problem encountered by existing methods, GP-Close employs the notion of generalization closure for systematic over...
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المؤلفون الرئيسيون: | , |
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التنسيق: | text |
اللغة: | English |
منشور في: |
Institutional Knowledge at Singapore Management University
2006
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الموضوعات: | |
الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/sis_research/6574 https://ink.library.smu.edu.sg/context/sis_research/article/7577/viewcontent/Jiang_Tan2006_Chapter_MiningRDFMetadataForGeneralize.pdf |
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المؤسسة: | Singapore Management University |
اللغة: | English |
الملخص: | In this paper, we present a novel frequent generalized pattern mining algorithm, called GP-Close, for mining generalized associations from RDF metadata. To solve the over-generalization problem encountered by existing methods, GP-Close employs the notion of generalization closure for systematic over-generalization reduction. Empirical experiments conducted on real world RDF data sets show that our method can substantially reduce pattern redundancy and perform much better than the original generalized association rule mining algorithm Cumulate in term of time efficiency. |
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