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arXiv · 1810.00326

Using Graph-Pattern Association Rules On Yago Knowledge Base

Wahyudi·Masayu Leylia Khodra·Ary Setijadi Prihatmanto·Carmadi Machbub
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Abstract

We propose the use of Graph-Pattern Association Rules (GPARs) on the Yago knowledge base. Extending association rules for itemsets, GPARS can help to discover regularities between entities in knowledge bases. A rule-generated graph pattern (RGGP) algorithm was used for extracting rules from the Yago knowledge base and a graph-pattern association rules algorithm for creating association rules. Our research resulted in 1114 association rules, where the value of standard confidence at 50.18% was better than partial completeness assumption (PCA) confidence at 49.82%. Besides that the computation time for standard confidence was also better than for PCA confidence

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Wahyudi, Masayu Leylia Khodra, Ary Setijadi Prihatmanto, Carmadi Machbub. 2018-09-30. Using Graph-Pattern Association Rules On Yago Knowledge Base. https://arxiv.org/abs/1810.00326

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