Abstract
The user profile contains different user information, such as personal information and interests. Research on profiling user interests can be divided into two groups. The first group builds the user interests based on the text extracted from browsing history (could generate a lot of false interests). The second group uses both user behavior and browsing history to determine his interests. The latter solution does not use enough factors (one or two factors only) and calculates the weight of each factor via predefined ranges, which generate a false factor weight and false user interests. In this paper, we propose an approach that employs Fuzzy Logic with several factors (scrolling speed, time spent, and the number of visits). This approach adapts the weight of each factor to the user habits, build and update the user profile from his browsing history. The results show that our approach significantly decreases the error rate.
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Silem, A.E.H., Taktak, H., Moussa, F. (2020). Dynamic User Interests Profiling Using Fuzzy Logic Application. In: Barolli, L., Amato, F., Moscato, F., Enokido, T., Takizawa, M. (eds) Advanced Information Networking and Applications. AINA 2020. Advances in Intelligent Systems and Computing, vol 1151. Springer, Cham. https://doi.org/10.1007/978-3-030-44041-1_84
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DOI: https://doi.org/10.1007/978-3-030-44041-1_84
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