Work

Using Graph Pattern Association Rules on Yago Knowledge Base

Year: 2019

Type: article

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.

Source: Journal of ICT Research and Applications

DOI: 10.5614/itbj.ict.res.appl.2019.13.2.6

Authors: Wahyudi Wahyudi, Masayu Leylia Khodra, Ary Setijadi Prihatmanto, Carmadi Machbub

Institution: Bandung Institute of Technology

Language: English

Topic: Data Mining Algorithms and Applications

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $150

OpenAlex ID: W2980004178

FWCI: 0.932

Cites: 18

Cited by: 3

Related to: 10