Mining Multirelation Association Rules on the Web of Data - de Oliveira, Felipe Alves (2020)
The Web of Data is a growing and relevant data source that contains information distributed in interconnected datasets. Most data mining algorithms were designed to analyze a single dataset at a time and, hence, cannot explore the connections between the datasets in the Web of Data. To overcome this limitation, the present work proposes MRAR+, a graph mining method that searches for multirelation association rules in order to identify new and useful knowledge involving resources of multiple datasets connected to the Web of Data. To illustrate MRAR+'s feasibility, this paper reports on two experiments where the proposed method mined different datasets interconnected in the Web of Data and produced new and useful rules for the users.