Semantic Web Rule Based Decision Support System: Knowledge Graph

Abstract

Recently, ontology has been constructed for information retrieval effectively from huge databases. Ontology shows the relationship of information. It is used to share, reuse and exchange domain knowledge to construct new ontology. Semantic web helps to solve the problem of semantic interoperability. The institution organizes a number of activities for student placement such as workshops, conferences, expert sessions, etc. The semantic web rule based decision support system ontology is constructed to predict students placement. First of all the data is collected from students. Next, the collected data is preprocessed. The J48 algorithm is used to classify the data. Further, the Expectation Maximization (EM) algorithm has been taken to form a cluster of classified data. Decision tree has been constructed using the J48 algorithm. Semantic web rules are constructed from a decision tree. The ontology is constructed in Protégé 5.5.0 and semantic web rules are added. Lastly, knowledge graphs of constructed systems have been graphically presented using VOWL, OntoGraf, OntoViz. This system will be helpful to the institute and students to track progress of placement.