Prediction of Users’ Behavior on the Web 2.0

We’re spending each day millions of social data. But this information is lost every day, and not used by the machine learning. In this paper, we’ll propose a way how we can use this data. Our goal is to get a person data, from social networks, by the aid of an API. Then analyze his profile, interactions, behaviors, interests, and comments. After that, we can make prediction of his future plans, and analyze his needs. Also, we can use make this predictions used by the shopping centers, Restaurants, Flight companies, Hotels, or any other establishment. We can offer for the person the best plans, according to his needs. The best solution, it’s to combine the social networks data, with a predictive engine such as Google prediction API. That’ll feed this last with a bunch of trained Data. Learning machines, for prediction have been already developed on the market. Some of them don’t have enough trained data, and most of them are dedicated to CRM’s. Our approach is at the opposite of the common, not dedicated to the CRM’s, but for the person itself. Our aim is not to increase the sales rates, but to help the users, and make an easy life for them. We can develop our solution more, and use it for the benefit of the entire society and the government also. We can use it for security, to predict acts of terrorism, strikes, robberies, revolutions.