Utilizing contextual ontological user profiles for personalized recommendations |
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| Affiliation: | 1. School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK;2. College of Computer Science and Engineering, University of Taibah, Medina, Saudi Arabia;1. Department of Computer Science and Information Engineering, National Cheng Kung University, 1, University Road, Tainan City 701, Taiwan, ROC;2. Department of Computer Science and Information Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung 80778, Taiwan, ROC;3. Cloud Service Technology Center, Industrial Technology Research Institute (ITRI South), Tainan, Taiwan, ROC;1. ISEGI, Universidade Nova de Lisboa, 1070-312 Lisboa, Portugal;2. INESC-ID, IST, University of Lisbon, 1000-029 Lisbon, Portugal;3. LabMAg, FCUL, University of Lisbon, 1749-016 Lisbon, Portugal;1. University of Information Technology, Vietnam National University, Ho Chi Minh, Viet Nam;2. Information Technology Department, Ton Duc Thang University, Ho Chi Minh, Viet Nam;3. Department of Computer Science, University of Science, Vietnam National University, Ho Chi Minh, Viet Nam;1. Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China;2. College of Computer Science, Zhejiang University, Hangzhou 310027, China;3. Stanford University, Stanford, CA 94305, USA;4. Hewlett-Packard Labs, 94304 Palo Alto, CA, USA;5. School of Finance and Economics, Zhejiang University of Finance & Economics, Dongfang College Jiaxing, Hangzhou 314408, China |
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| Abstract: | As users may have different needs in different situations and contexts, it is increasingly important to consider user context data when filtering information. In the field of web personalization and recommender systems, most of the studies have focused on the process of modelling user profiles and the personalization process in order to provide personalized services to the user, but not on contextualized services. Rather limited attention has been paid to investigate how to discover, model, exploit and integrate context information in personalization systems in a generic way. In this paper, we aim at providing a novel model to build, exploit and integrate context information with a web personalization system. A context-aware personalization system (CAPS) is developed which is able to model and build contextual and personalized ontological user profiles based on the user’s interests and context information. These profiles are then exploited in order to infer and provide contextual recommendations to users. The methods and system developed are evaluated through a user study which shows that considering context information in web personalization systems can provide more effective personalization services and offer better recommendations to users. |
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| Keywords: | User profiles Context-aware systems Web personalization Recommender systems |
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