Xuemeng Song

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We are living in the era of social networks, where people throughout the world are connected and organized by multiple social networks. The views revealed by different social networks may vary according to the different services they offer. They are complimentary to each other and comprehensively characterize a specific user from different perspectives. As(More)
User interest inference from social networks is a fundamental problem to many applications. It usually exhibits dual-heterogeneities: a user's interests are complementarily and comprehensively reflected by multiple social networks; interests are inter-correlated in a nonuniform way rather than independent to each other. Although great success has been(More)
Volunteers are extremely crucial to nonprofit organizations (NPOs) to sustain their continuing operations. On the other hand, many talents are looking for appropriate volunteer opportunities to realize their dreams of making an impact on the world with their expertise. This is a typical supply and demand matching issue. Fortunately, user profiling and the(More)
Volunteers have always been extremely crucial and in urgent need for nonprofit organizations (NPOs) to sustain their continuing operations. However, it is expensive and time-consuming to recruit volunteers using traditional approaches. In the Web 2.0 era, abundant and ubiquitous social media data opens a door to the possibility of automatic volunteer(More)
Social networks contain a wealth of useful information. In this paper, we study a challenging task for integrating users' information from multiple heterogeneous social networks to gain a comprehensive understanding of users' interests and behaviors. Although much effort has been spent to study this problem, most existing approaches adopt linear models to(More)
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