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Computer Sciences

Turkish Journal of Electrical Engineering and Computer Sciences

User profiling

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Full-Text Articles in Computer Engineering

User Profiling For Tv Program Recommendation Based On Hybrid Televisionstandards Using Controlled Clustering With Genetic Algorithms And Artificial Neuralnetworks, İhsan Topalli, Selçuk Kilinç Jan 2020

User Profiling For Tv Program Recommendation Based On Hybrid Televisionstandards Using Controlled Clustering With Genetic Algorithms And Artificial Neuralnetworks, İhsan Topalli, Selçuk Kilinç

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, an earlier method proposed by the authors to make smart recommendations utilizing artificial intelligence and the latest technologies developed for the television area is expanded further using controlled clustering with genetic algorithms (CCGA). For this purpose, genetic algorithms (GAs), artificial neural networks (ANNs), and hybrid broadcast broadband television (HbbTV) are combined to get the users' television viewing habits and to create profiles. Then television programs are recommended to the users based on that profiling. The data gathered by the developed HbbTV application for previous studies are reused in this study. These data are employed to cluster users. …


A Model For User Profiling Systems With Interacting Agents, Sanem Sariel, Tevfi̇k Akgün Jan 2005

A Model For User Profiling Systems With Interacting Agents, Sanem Sariel, Tevfi̇k Akgün

Turkish Journal of Electrical Engineering and Computer Sciences

Service systems according to users' personal demands and preferences are on their way to provide required services in many application domains. Emulation of interactive model of human societies produces valuable outcomes for such systems. In this work, a system model with interactive agents for multi user service systems is proposed. A novel social interactive agent model using different interaction forms is also included in this proposal. In this model, agents decide how to serve to their users by considering their users' profiles and information from other agents. User clusters are formed by clustering techniques. The Q-learning algorithm is used for …