Enhancing the performance of web Focused CRAWLer Using Ontology

The enormous growth of the World Wide Web in the recent years has made it important to perform resources discovery efficiently. The rapid growth of World Wide Web poses (Doubles in size approximately every eight months) unprecedented scaling challenges for general purpose crawler and search engine. Finding useful information from the web which has a large and distributed structure required efficient search strategies. As ontology plays an important role in providing controlled vocabulary of concepts, each with an explicitly defined and machine process able semantics. In this paper ,we propose the novel concept of intelligent crawling of Ontology based content focused crawling , the new approach that analyses it crawl boundary to find the links that are likely to be the most relevant for the crawl? while a boundary irrelevant region of the web. Through our new focused crawling technique we solve the polysemy (refer to word with multiple meaning) and synonymy (refers to multiple word having the same meaning) semantic net problem. Also instead of searching in the whole web, our proposed technique will search in the ontology build by us that is updated periodically after a very short interval than instead of displaying all the information that is not related to the user need, we will display only relevant and related information. Our purposed work give us two? fold benefit , firstly only focused result are retrieved? which reduce the number of results entreated and secondly, due to focused searching irrelevant result are pruned which reduce the time.