Chun Chen

TL;DR: A graph based algorithm, called graph regularized sparse coding, is proposed, to learn the sparse representations that explicitly take into account the local manifold structure of the data.

TL;DR: A novel propagation approach is proposed that exploits the relations between sentiment words and topics or product features that the sentiment words modify, and also sentiment Words and product features themselves to extract new sentiment words.

TL;DR: Experimental results show that the proposed framework consistently gives better performance than state-of-the-art approaches without sacrificing training or inference complexity, demonstrating the effectiveness of the proposed two-level distillation framework.

TL;DR: A novel music recommendation algorithm is proposed by using both multiple kinds of social media information and music acoustic-based content, and uses hypergraph to model the various objects and relations, and considers music recommendation as a ranking problem on this hypergraph.