We propose a generative model based on latent Dirichlet allocation for mining distinct topics in document collections by integrating the temporal ordering of documents into the ge...
Levent Bolelli, Seyda Ertekin, Ding Zhou, C. Lee G...
Recent research has shown that collective classification in relational data often exhibit significant performance gains over conventional approaches that classify instances indi...
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
How to effectively protect against spam on search ranking results is an important issue for contemporary web search engines. This paper addresses the problem of combating one majo...
Guoyang Shen, Bin Gao, Tie-Yan Liu, Guang Feng, Sh...