Using Machine Learning Techniques to Customize the User\u27s Profile, Helps Intelligent TV Decoder’s Design

In today\u27s society due to the increase of the quantity of information is becoming more difficult to find the information we search. Data mining offers us the most important methods and techniques in data analysis. Through this work, we aim to study the several data mining techniques, methods and applications in specific areas. We experiment with an “open software WEKA, to perform some data analysis, presenting the reliability and advantages of data mining classification technique. We use the decision trees technique to achieve the task of classification, to customize user profiles based on their requirements and needs. This paper presents also how machine learning methods can be integrated with agent technology in building more intelligent agents. Using machine learning techniques makes it possible to develop agents able to learn from and adapt to their environment. So a TV decoder can be adapted to the demands of TV viewers. If the decoder initially trained by the demands and needs of viewers, it can display intelligent behavior, suggesting viewers, according to the profile created for each one, shows and movies. The paper concludes with our contributions concerning the application of data mining techniques to customize services according to the requirements and needs of users