Dual-Stage Social Friend Recommendation System Based on User Interests

Recommendation of scholarly venues based on dynamic user interests

It is no secret that the number of scholarly events and venues available for researchers is and has been dramatically expanding. While this tremendous expansion is certainly a boon for academia as a whole, it has become increasingly difficult for many researchers to identify events and venues related to their work. Therefore, as opportunities to share scholarly work continue to expand, research...

Facebook user interests exploration and recommendation based on Facebook Social Graph data analysis

Because of the dynamic evolution and propagation of the Internet and the popularization of social networks, huge amounts of information about the users of the Internet are easily accessible to anyone. The most popular social networks provide efficient and easy to use tools that allow to interact with their users, as well as access profile data. This type of information just several years ago wa...

Service Recommendation with Adaptive User Interests Modeling

In composing and using services, user’s requirements are subject to uncertainty and changes. It can be difficult for users to maintain an overview of all available services and to make good choices among them. This paper proposes an approach to proactively recommending suitable services to users. Our major contribution is to have devised a novel user-interest model to describe user’s interests ...

Scalable and Explainable Friend Recommendation in Campus Social Network System

With the increasing popularity of social network systems, it’s valuable and important to provide well-designed and effective friend recommendation for users to achieve high loyalty of them. Although FOF is an effective and widely used friend recommendation algorithm, the straight-forward implementation of it needs increasingly large amount of computation power with the growth of the number of u...

Enabling Personalized Recommendation on the Web based on User Interests and Behaviors