An Ontology Based Text-Mining to Clustering the Research Projects Based on Fuzzy Technique

Abstract

Both the internet and the intranets contain more resources and they are called as text documents. Research and development (R&D) scheme selection is a type of decision-making normally present in government support agencies, research institutes, technology intensive companies and universities. Text Mining has come out as an authoritative technique for extracting the unknown information from the large text document. Ontology is defined as a knowledge storehouse in which concepts and conditions are defined in addition to relationships between these concepts. Ontology's build the task of searching alike pattern of text that to be more effectual, efficient and interactive. The present method for combine proposals for selection of research project is proposed by ontology based text mining technique to the data mining approach of cluster research proposals support on their likeness in research area. Though the research proposal regarding particular research area is cannot always be accurate. This paper proposes an ontology based text mining to group required data such as research proposals and external reviewers based on their research area. The proposed method like Fuzzy SOM and the NRGA algorithm is used to cluster here. The proposed method is efficient and effective for clustering research proposals.  The experimental result is evaluated based on F-measure which proves that the proposed approach gives improved results.