Ontology Based Text Mining Method Using Cluster Approach

In the present world, due to tremendous development in technology, a huge amount of information is available everywhere. Therefore, it is difficult for the users to understand the main content of the entire document as it takes a lot of time. Our project uses the extractive text summarization which uses a method to give the version of summary for one or more file or document. Here we give an approach that maps sentences to nodes of a hierarchical ontology. Ontology explains what exists in a particular domain. For the ontology creation, vocabularies and synonyms are collected. It is used as background knowledge and helps to find the related meaning of the terms which occur in the source documents. Text mining is the technique from which high-quality information is derived from text. Clustering is a significant task. The clustering method groups similar or related terms into a single group. In the first stage, data collection takes place. The preprocessing stage includes stemming and stop words removal.TF-IDF process occurs after which clustering takes place. In the ontology creation, first the determination of the main sub topics of the article of interest is done. Further, the project will extend by giving the refined graph and the summarized text.