Using Graph-Pattern Association Rules On Yago Knowledge Base
Databases
2018-10-02 v1
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
Keywords
Cite
@article{arxiv.1810.00326,
title = {Using Graph-Pattern Association Rules On Yago Knowledge Base},
author = {Wahyudi and Masayu Leylia Khodra and Ary Setijadi Prihatmanto and Carmadi Machbub},
journal= {arXiv preprint arXiv:1810.00326},
year = {2018}
}