RDF-ML: A Proposed SPARQL Tool for Machine Learning on Semantic Web Data

Abstract

Semantic web data is a core data representation format in different technologies over web like linked open data, social networks, and knowledge graph databases. It will give the strength to these technologies while incorporating machine learning power on those data. W3C community is also working in this direction while constructing a group of SPARQL-ML. RDF-ML is a proposed web based tool which contains the capability of SPARQL processing engine. Through this tool machine learning can be applied on the built-in as well as user defined datasets in the form of RDF. This tool will produce faster results for the research community, working in the domain of semantic web and wants to produce results while applying machine learning and interpret them. This paper brief about the tool, it's utility with the aspect for SPARQL query processing along with machine learning. This paper proposed a framework for RDF-ML tool and represents the working of tool with snapshots and comparison for machine learning model on RDF data.