Here, I am pleasure to introduce Bi Chen, 陈碧, in Chinese, a 3rd PhD. student working with Dr. Xiaolong (Luke) Zhang, the same advisor as me.
Bi entered IST as a doctoral student in IST in 2006. Prior to that, he earned his B.S and M.S in computer science and communications at Zhejiang University, a beautiful university in China (See figure bellow).
At that time, he began pursuing the topic how to utilize computing
techniques predict and leverage social behaviors. Right now, he is
working on his dissertation proposal.
He has attended 3 conferences: 15th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises (WETICE 2006), 26-28 June 2006, Manchester, United Kingdom; IEEE International Conference on Data Mining (ICDM 2007); and 22nd AAAI Conference on Artificial Intelligence (AAAI 2007), July 22-26, 2007, Vancouver, British Columbia, Canada. The conferences he attended focus on data mining and artificial intelligence.
3 publications have been done by Bi so far (some details can be obtain via DBLP):
1. Bi Chen, He Tan, Patrick Lambrix: Structure-Based Filtering for Ontology Alignment. WETICE 2006: 364-369
2. Bi Chen, Qiankun Zhao, Bingjun Sun, Prasenjit Mitra: Predicting Blogging Behavior Using Temporal and Social Networks. ICDM 2007: 439-444
2006
3. Qiankun Zhao, Prasenjit Mitra, Bi Chen: Temporal and Information Flow Based Event Detection from Social Text Streams. AAAI 2007: 1501-1506
He orients himself more on the technical vertex of the Great Triangle of IST, but also incorporating social factors. This is easily perceived from his recently publication and dissertation topic, which is about modeling social behavoirs, especially in social networks, with data mining techniques. Right now, he is also considering more human factors and interactions when constructing data mining model.
Academically, I can benefit a lot from his work. My research interest is also about social networks sense making, but from another perspective: information visualization. I am trying to utilize network visualization and interaction techniques to understand the huge social network data. A big challenge here is how to employ the semantic data attached to the actors in social networks to facilitate the understanding of social networks when visualizing them. A potential solution is to extract the semantic content and also consider the structure of social network to leverage the visual representation of social networks and data attached them. In this sense, the data mining techniques, combining some linguistic computation techniques could offer me a good venue to address this issue. This area is exact strength of Bi Chen's works.
Bi entered IST as a doctoral student in IST in 2006. Prior to that, he earned his B.S and M.S in computer science and communications at Zhejiang University, a beautiful university in China (See figure bellow).
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He has attended 3 conferences: 15th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises (WETICE 2006), 26-28 June 2006, Manchester, United Kingdom; IEEE International Conference on Data Mining (ICDM 2007); and 22nd AAAI Conference on Artificial Intelligence (AAAI 2007), July 22-26, 2007, Vancouver, British Columbia, Canada. The conferences he attended focus on data mining and artificial intelligence.
3 publications have been done by Bi so far (some details can be obtain via DBLP):
1. Bi Chen, He Tan, Patrick Lambrix: Structure-Based Filtering for Ontology Alignment. WETICE 2006: 364-369
2. Bi Chen, Qiankun Zhao, Bingjun Sun, Prasenjit Mitra: Predicting Blogging Behavior Using Temporal and Social Networks. ICDM 2007: 439-444
2006
3. Qiankun Zhao, Prasenjit Mitra, Bi Chen: Temporal and Information Flow Based Event Detection from Social Text Streams. AAAI 2007: 1501-1506
He orients himself more on the technical vertex of the Great Triangle of IST, but also incorporating social factors. This is easily perceived from his recently publication and dissertation topic, which is about modeling social behavoirs, especially in social networks, with data mining techniques. Right now, he is also considering more human factors and interactions when constructing data mining model.
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Bige is so good, I like him!