Exploiting User Interests to Characterize Navigational Patterns in Web Browsing Assistance |
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Authors: | Daniela Godoy Analía Amandi |
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Affiliation: | (1) ISISTAN Research Institute, UNICEN University, Campus Universitario, Paraje Arroyo Seco, CP 7000 Tandil, Bs. As., Argentina;(2) CONICET, Consejo Nacional de Investigaciones Científicas y Técnicas, CP 1033, Capital Federal, Bs. As., Argentina |
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Abstract: | In order to be capable of exploiting context for pro-active information recommendation, agents need to extract and understand
user activities based on their knowledge of the user interests. In this paper, we propose a novel approach for context-aware
recommendation in browsing assistants based on the integration of user profiles, navigational patterns and contextual elements.
In this approach, user profiles built using an unsupervised Web page clustering algorithm are used to characterize user ongoing
activities and behavior patterns. Experimental evidence show that using longer-term interests to explain active browsing goals
user assistance is effectively enhanced.
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Keywords: | User Profiling Context-awareness Browsing Assistants |
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