Estimating user interaction strength in distributed online networks

Abstract

SUMMARYUser interactions are indispensable for any online network to thrive, especially for BitTorrent-like and Web real-time communication-based distributed online networks that rely on users' collective contributions instead of the help of central servers. User interactions provide fine-grained information for many applications, such as security enhancement and cooperation promotion. To date, several schemes for estimating user interaction strength in centralized online networks have been proposed. In contrast, we present design, deployment, and analysis of UISE for user interaction strength estimation in distributed online networks. Among the strong points of UISE is that it captures both direct and indirect user interactions, and that it scales with only partial information dissemination. We apply UISE to devise the first distributed scheme for online time estimation and we implement it into Tribler, a distributed online network for media and social applications like file sharing, streaming, and voting. We demonstrate the accuracy and the scalability of UISE with different information dissemination protocols and user behaviors using simulations, emulations, and a real-world deployment.

Event space model in virtual and real society based on special field

“…The Internet information easy-to-catch, the data complex and value sparse features caused a large number of scholars have interested in web data mining research. However, the incomplete data with sparse feathers posts the following challenging issues: (1) how to accurately describe an event by multi-view, and (2) how to effectively track an event by detecting it during times.…”

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