This paper presents WIA-Opinmine system developed by CUHK_Tsinghua Web Information Analysis (WIA) Virtual Research Center for NTCIR-8 MOAT Task. The system is deemed special due to three facts. Firstly, the system is able to handle Simplified Chinese and Traditional Chinese at the same time. A tool is developed to convert Traditional Chinese into Simplified Chinese before opinion analysis. Secondly, a topic model based algorithm is found effective in relevance judgment. A co-clustering algorithm is incorporated in topic modeling. Thirdly, a ranking method is adopted to rank all holder (A0's) and target (A1's) candidates recognized by a semantic role labeling tool during which topic models for each topic are fully used for judging the importance of all candidates. The NTCIR8 evaluation results as well as the post-NTCIR8 results show that our system could effectively recognize relevance sentences, opinionated sentences and polarities.