Information retrieval is used to find a subset of relevant documents against a set of documents. Determining semantic similarity between two terms is a crucial problem in Web Mining for such applications as information retrieval systems and recommender systems. Semantic similarity refers to the sameness of two terms based on sameness of their meaning or their semantic contents. Recently many techniques have introduced measuring semantic similarity using Wikipedia, a free online encyclopedia. In this paper, a new technique of measuring semantic similarity is proposed. The proposed method uses Wikipedia as an ontology and spreading activation strategy to compute semantic similarity. The utility of the proposed system is evaluated by using the taxonomy of Wikipedia categories.
Title = "Semantic Information Retrieval based on Wikipedia Taxonomy",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "2",
Pages ="1 - 85",
Year = "2013",
Authors ="May Sabai Han"}