Abstract
Personalized search utilizes the user context in a form of profile to increase the information retrieval accuracy with user’s interests. Recently, semantic search has greatly attracted researchers’ attention over the traditional keyword-based search because of having capabilities to figure out the meaning of search query, understanding users’ information needs accurately using semantic web technology. In this paper, a ODP (open directory project)-based approach for personalized semantic information search is proposed. A reference ontology is generated by utilizing ODP to model user’s interests and semantic search space. User profile is initially derived by matching between user’s details and the reference ontology to model his/her interests and preference. Semantic search space is constructed by fuzzily classifying documents into the reference ontology. We also present an evaluation of our proposed method which indicates a considerable improvement of search accuracy with the field of application human judgment.
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Duong, T.H., Uddin, M.N., Nguyen, C.D. (2013). Personalized Semantic Search Using ODP: A Study Case in Academic Domain. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2013. ICCSA 2013. Lecture Notes in Computer Science, vol 7975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39640-3_44
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DOI: https://doi.org/10.1007/978-3-642-39640-3_44
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