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VERDIKT-Kjernekomp.og verdiskaping IKT

Social Networks Based Recommendation Engine

Awarded: NOK 0.76 mill.

The overall goal of this project is to create a scalable social network games based datamining solution with state of the art analysis-module on top. The module will provide intelligent and optimal recommendations (friends, digital in-game items, actions, etc) for any given player at any stage in the game, as well as giving recommendations to the company running the game. The module will work with new business models like virtual goods, free-to-play and hybrids as well as upcoming models which we plan to develop in the wake of this project. In essence, the recommendation engine consists of these parts: 1. Stored behavior data: Huge amounts of social network behavior data will be logged 2. Engine: State of the art data analyzing by real-time engine 3. Re commendations: Engine recommends optimal solutions for the user and the service host This project initiates comprehensive and interesting research work, but in the long run, it is the users that will benefit from greater online experiences. The result wi ll be better social interaction, improved ease of use and higher fun-factor in the products. The Social Network Games have seen a huge growth the last years. "Inside Virtual Goods" describes the situation like this: "2010 will be remembered as the year that games on social networks became a billion dollar business and transformed the way millions more people socialized with friends online ... Despite the challenges facing the market, it's become clear that there are still substantial opportunities for social game developers with virtual goods revenue models, but the market is still evolving rapidly." Games are a major part of the future social networks, and the games-industry is likely to once again spearhead new business models. Models which we expec t will move into other online industries years later.

Funding scheme:

VERDIKT-Kjernekomp.og verdiskaping IKT