An ontology-based text-mining method to develop intelligent information system using cluster based approach

Text clustering is an important task. Generally, text document clustering methods attempt to segregate the documents into groups where each group represents some topic if the topics are same then they are belonging in the same group if the topics are different then new group can be created with the help of cluster and that different topic store in new group. In this paper has present an clustering on ontology based text mining for grouping paper or proposals and assigning that grouped proposal to reviewers systematically. It facilitates text-mining and some text extraction techniques to cluster approach based on their similarities and then to assign them to reviewer and obtain text summarization. A principled approach is proposed to develop an intelligent information system by analyzing the unstructured repair verbatim data. Construct the fault diagnosis ontology for find out the fault so that extract the irrelevant information. The three text mining technique can be used for creating intelligent information system. The proposed method is that analysis of text summarization and plagiarism analysis and find out the efficiency i.e. time complexity and increase the performance of system using cluster based approach.