A Semantic Search Engine for Learning Resources

In this paper we present an architectural overview of a search engine based on semantic web technologies to improve the search for learning resources. The use of search engines has contributed to the success of the Web. At present, many people use search engines to retrieve relevant information about a topic and students also use search engines to find learning resources. Keyword-based searches present several problems related to the meaning of the keyword used in the search query, these limits can be overcome by applying semantic web technologies to search engines. Semantic web meta-data can be used in e-learning fields to enrich the information content of the learning object and to develop a better search methodology. A semantic search engine can elaborate search queries semantically to find conceptual relations between documents and to retrieve learning resources in a more efficient way.