Temporal dynamic study in personalization digital newspaper ??ahora!


In recent years the utilization of Recommender Systems has greatly increased, and with it the investigations in this space. Each time investigators attempt tougher to find techniques and tools that permit improving the performance of said systems. One of the principal problems that investigators face in this field is the continuous modification of the users' preferences throughout time, whose analysis supposes an approach to the tastes and preferences of the users. In the current investigation the target is the planning of a model for Recommender Systems in collaborative filtering with temporary dynamics. The proposed model is developed with the utilization of a Hidden Markov Model. This technique is used with the goal of tracking the continuous amendment in the users' preferences in time. The proposed resolution is described moreover because the experimentation distributed to validate the model. The obtained results show a higher performance of the proposed model that includes the temporary dynamics on the bottom model that doesn't have this in mind.

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