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Masayu Leylia Khodra
School of Electrical Engineering and Informatics, Institut Teknologi Bandung Jalan Ganesha 10, Bandung 40132,
Computer Science & IT

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Using Graph Pattern Association Rules on Yago Knowledge Base Wahyudi Wahyudi; Masayu Leylia Khodra; Ary Setijadi Prihatmanto; Carmadi Machbub
Journal of ICT Research and Applications Vol. 13 No. 2 (2019)
Publisher : LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.ict.res.appl.2019.13.2.6

Abstract

The use of graph pattern association rules (GPARs) on the Yago knowledge base is proposed. Extending association rules for itemsets, GPARS can help to discover regularities between entities in a knowledge base. A rule-generated graph pattern (RGGP) algorithm was used for extracting rules from the Yago knowledge base and a GPAR algorithm for creating the association rules. Our research resulted in 1114 association rules, with the value of standard confidence at 50.18% 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.
Co-Authors Ary Setijadi Prihatmanto Carmadi Machbub Wahyudi Wahyudi