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Millions of people play Massively Multiplayer Online Games (MMOGs) and participate in the social networks built around MMOGs daily. These players turn into a collaborative com-munity to exchange game news, advice, and expertise, but in return expect support such as player reports and clan statistics. Thus, the MMOG social networks need to collect and analyze MMOG data, in a process of continuous MMOG analytics. With the appearance of cloud computing, it has become attractive to use on-demand resources to run automated MMOG data analytics tools. In this work the authors present CAMEO, an architecture for Continuous Analytics for Massively multiplayEr Online games on cloud re-sources. The architecture provides various mechanisms for MMOG data collection and continuous analytics of a pre-determined accuracy in real settings.
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