Automated populates and updates personalized ontology with analysis result

Abstract

To work effectively, the semantic web make explicit resources via ontologies. Semantic web is intended to make the machines to progress information themselves by understanding its significance. Ontology offers a shared collective understanding of application domain in concise and consensual manner. Ontology serves as a knowledge base domain by instantiating its concepts and semantic query language retrieves the information from the domain. The problem addressed in this paper is the challenge of automated populating and SPARQL query generator ontology given the type of input and retrieve the mandatory information from the personalized ontology. We propose personalized automated ontology for Non-Governmental Organization (NGO) system using Top-down methodology. An NGO is legally organized corporations that function independently from any form of government developed by likely or authorized persons. We propose an algorithm to populate and update ontology constantly based on user input as the requirement changes over time. Note to Practitioners - We develop Ontology by gathered information about various NGO's and built in owl language using protégé tool. The personalized NGO ontology is created by Top-Down Methodology. The users' natural language queries are automatically converted into equivalent SPARQL queries to retrieve information from ontology. To convert user query into SPARQL queries we used QuriOnto and Kuntt Moris Pratt algorithms. Using populate and update algorithm the NGO ontology can be modified constantly based on user input as the requirement changes over time. We develop event-based user interface for easy usage of ontology system. The personalized NGO ontology data are evaluated and result demonstrated in graphical forms. This System offers proper information for people approaching NGOs for fund raising or for benefit.