A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...
Topic distillation is one of the main information needs when users search the Web. In previous approaches to topic distillation, the single page was treated as the basic searching ...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Guang Feng, W...
In this paper, we propose a new probabilistic generative model, called Topic-Perspective Model, for simulating the generation process of social annotations. Different from other g...
Caimei Lu, Xiaohua Hu, Xin Chen, Jung-ran Park, Ti...
Multi-Document Summarization deals with computing a summary for a set of related articles such that they give the user a general view about the events. One of the objectives is th...