A semantic based approach to organize eLearning through efficient information retrieval for interview preparation

Of all available sources to enrich people's knowledge, Internet stacks us with bundles of information about the searched one. This ton of results is not a problem till we are very keen to obtain knowledge from our search. Concerning with students all over the world, the next move is the obtainment of a job, which makes them stand independently and prepare themselves to start up their life. But when the student sits and searches materials to prepare for interview, they find it very difficult to get a clear idea as the information that we require is almost not got in a unified environment and are scattered inclusive of the forum pages, or the one with irrelevant contents. As an initial step in a ladder of enriched environment for knowledge up-gradation this paper implements a tool enhancing a refined search retrieving only the most relevant links eliminating the other links using the semantic web technologies. The soul idea is to define ontologies for various companies and gather learning objects using EXTRACT URL tool to build up the knowledge base. These are ranked using AHP technique and assembled in RDF data model. The user's search text is stemmed and compared with attributes defined in ontology. Using JENA API's, the SPARQL query is now dynamically built, one for collecting all relevant links and the other providing the most relevant links by generating queries for all combinations of search text thus refining the search with increased Precision and Recall rates.