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People and entity retrieval in implicit social networks

机译:隐式社交网络中的人员和实体检索

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Online social networks can be viewed as implicit real world networks, that manage to capture a wealth of information about heterogeneous nodes and edges, which are highly interconnected. Such abundant data can be beneficial in finding and retrieving relevant people and entities within these networks. Effective methods of achieving this can be useful in systems ranging from recommender systems to people and entity discovery systems. Our main contribution in this paper is the proposal of a novel localized algorithm that operates on the sub graph of the social graph and retrieves relevant people or entities. We also demonstrate how such an algorithm can be used in large real world social networks and graphs to efficiently retrieve relevant people/entities.
机译:在线社交网络可以被视为隐含的现实网络,这些网络可以捕获有关具有高度互连的异构节点和边的大量信息。这种丰富的数据可以有利于在这些网络中寻找和检索相关人员和实体。实现这一目标的有效方法可以在从推荐系统到人员和实体发现系统的系统范围内有用。我们本文的主要贡献是提出了一种新颖的本地化算法,这些算法在社会图的子图上运行,并检索相关人员或实体。我们还展示了在大型真实世界社交网络和图表中使用这种算法,以有效地检索相关人员/实体。

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