Developing a recommender system based on the social network "VKontakte" profile data

The following article considers the problem of web-surfing automation and content filtration. The principal objective of this project is to develop a software solution to this problem - a multi-agent system for analyzing VKontakte users’ interests - and providing a recommendation system EZSurf. The article describes the development and application of a multi-agent recommender system EZSurf that performs analysis of interests and provides recommendations for the social network VKontakte users based on the data from the profile of a particular user. The article also provides an analysis of different methods, technological solutions, and similar products aimed at content filtration, as well as their advantages and disadvantages. EZSurf allows automating the web-surfing process and content filtration with the use of user’s profile in a particular social network to collect data and API of external services (LastFM, TheMovieDB). For search and selection of information an agent (Recommender) that works as web-crawler has been implemented...