Real-Time Multi-Criteria Social Graph Partitioning

摘要: Graph partitioning has attracted considerable attention due to its high practicality for real-world applications. It is particularly relevant social networks because it enables the grouping of users into communities market analysis and advertising purposes. In this paper, we introduce RMGP, a type real-time multi-criteria graph that groups based on their connectivity similarity set input classes. We consider RMGP as an on-line task, which may be frequently performed different query parameters (e.g., classes). order overcome serious performance issues associated with large graphs found in practice, develop solutions game theoretic framework. Specifically, each user player, whose goal find class optimizes his objective function. propose algorithms best-response dynamics, analyze properties, show efficiency effectiveness real datasets under centralized decentralized scenarios.