Text Document Clustering with Ontology Applying Modify Concept Weighting

With the increasing amount of information, researchers in digital communities have witnessed the tremendous growth of publications. The overwhelming amount of information still makes it a time-consuming task. There are many of computer science and medical subject related documents cited on the Internet. Ontologies currently are hot topics in the area of Semantic Web. Ontologies can also help in addressing the problem of searching related entities, including research publications. The purpose of the system is to cluster the text documents based upon the ontology. The system is applying the modified concept weighting and become the extended version of the work that has been done before [8]. After the time passed the testing amount of data becomes lager and the challenges is the time complexity. To overcome this issue the system used the scoring method at the concept weighting stages to manage the time complexity. The experiments reveal that even the testing documents increased; the system may actually be able to produce useful result for text document clustering.