AISECT University , Bhopal Ph.D. scholar Computer Sc. Department,
While phenomenally successful regarding size and number of users, today's World Wide Web is fundamentally a relatively straightforward artifact. Web content consists mainly of distributed hypertext and hypermedia and is accessed via a combination of keyword based search and link navigation. The explosion in both the range and quantity of web content has, however, highlighted some serious shortcomings in the hypertext paradigm. Every year, the number of documents on the Internet is increasing, presenting the correct information at the right time in the most appropriate form is important, and it results in better browsing experience for users. To deal with this issue, ontology’s are proposed for knowledge representation, which is nowadays the backbone of semantic web applications. This is a challenging task as it requires complex queries to be answered with only a few keywords. Furthermore, it should allow the inferred knowledge to be retrieved easily and provide a ranking mechanism to reflect semantics and ontological importance. Proposed paper gives. A technique to improve the efficiency of matching web data with background knowledge.It finds correspondences between semantically related entities of ontology.
Shweta Shrivastava , Dr. Sanjay Agrawal. (2017). Searching of Web Data Using Ontological Matching. International Journal of Computer Engineering In Research Trends , 4(7), 296-300. Retrieved from http://ijcert.org/ems/ijcert_papers/V4I7003.pdf
: Semantic Web, Ontology, Information Retrieval, inferred knowledge, ranking mechanism, Web Search.
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