engleski

A Multi-Agent System for Games Trading on B2B Market Based on Users' Skills and Preferences

Since the amount of content offered to users by service providers is rapidly rising every day, it is not an easy task for users to find content which would fit their interest. To deal with that problem, personalization services are being developed which monitor users’ content consumption in order to try to offer content which is believed to correspond to preferences of a certain user. Alongside the problem that it is difficult for users to find the appropriate content, it is also difficult for service providers to procure and offer content for which users could be interested in. In this paper we focus on one content type - games for mobile phones and propose a model which enables analyzing data collected while users are playing a game. By using the results of the analysis, our model enables recommending new games to users, and also, what is the focus of this paper, acquiring new games which would fit users’ skills and preferences. By purchasing distribution rights for new games which are believed to be appropriate for users, service provider can be more certain that the offered games would be widely adopted.

multi-agent system; business-to-business market; personalization services; users’ skills and preferences

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