Semantic Information Retrieval: An Ontology and RDF-based Model

Retrieving the specific knowledge from the Web becomes a challenging task as it contributes enormous amounts of unorganized textual data. This paper focuses on lessening the time consumed by the user for searching the documents and providing the results as per user intention. This paper demonstrates a semantic query language SPARQL to extract the data from the student career knowledge base constructed using Resource Description Framework (RDF) that gives relevant information to the user. This paper provides the requested information by understanding user’s query intention with the created career ontology using RDF and SPARQL in a semantic manner. General Terms Semantic Information Retrieval, Semantic Web, Cognitive analysis, Machine Learning