ExpertNet : Searching Collaborative Social Networks

In modern life, due to the increasing complexity of tasks and accuracy of labor division, the situation that one problem can be solved by a single person has become history. Instead, problem resolution is the result of dynamic social collaboration of multiple experts toward a unified goal. With the emerge of Web 2.0, such collaborations become inter-disciplinary and global.

Understanding experts' skills, influence and their interactions in a collaborative social network that drives problem-solving processes is the key to find the right experts and thus to accelerate problem resolution and decision making. However, studies of collaborative innovation networks have been so far limited to be qualitative, based on questionnaire and surveys, which are subjective, inaccurate and costly.

In this research, we are developing computational foundations and quantitative frameworks to model, optimize, and search collaborative social networks to expedite problem-solving and to enhance team collaboration. Specifically, we address the following problems:

1. Modeling Collaborative Social Networks according to Historical Interactions
2. Quantitatively Profiling Experts and Relations in the Networks
3. Optimizing Problem Routing for Expert Search in the Networks

• Yichuan Cai and Yi Chen. Mining influential bloggers: From general to domain specific, from explicit to implicit. International Journal of Knowledge-Based and Intelligent Engineering Systems (KES), 16(4): 223-233 (2012).
• Yi Chen, Shu Tao, and Xifeng Yan. "Problem-Solving in Collaborative Social Networks".Invited Paper. PersDB Workshop (Personalized Access, Profile Management, and Context Awareness in Databases), 2011.
• Brian Ackerman, and Yi Chen. "Evaluating Rank Accuracy based on Incomplete Pairwise Preferences". Workshop of User-Centric Evaluation of Recommender Systems and Their Interfaces (UCERSTI), 2011.
• Gengxin Miao, Louise E. Moser, Xifeng Yan, Xifeng Yan, Yi Chen, and Nikos Anerousis. Generative Models for Ticket Resolution in Expert Networks. In Proceedings of the 16th International Conference on Knowledge Discovery and Data Mining (SIGKDD 2010): 733-742.
• Peng Sun, Shu Tao, Xifeng Yan, Nikos Anerousis, and Yi Chen. "Content-Aware Resolution Sequence Mining for Ticket Routing". In Proceedings of the 8th International Conference on Business Process Management (BPM), 2010.
• Yi Chen, Shu Tao, Xifeng Yan, Nikos Anerousis, and Qihong Shao. "Assessing Expertise Awareness in Resolution Networks".In Proceedings of the International Conference on Social Networks Analysis and Mining(ASONAM 2010).
• Yichuan Cai, Yi Chen. "MASS: a Multi-fAcet domain-Specific influential blogger mining System"Demo Description. In Proceedings of the 26th IEEE International Conference on Data Engineering (ICDE), 2010.
• Yichuan Cai, Yi Chen. "Mining Influential Bloggers: From General to Domain Specific". In Proceedings of 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES), 2009.
• Qihong Shao, Yi Chen, Shu Tao, Xifeng Yan, and Nikos Anerousis. Efficient Ticket Routing by Resolution Sequence Mining. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (SIGKDD 2008): 605-613.
• Qihong Shao, Yi Chen, Shu Tao, Xifeng Yan, and Nikos Anerousis. "EasyTicket: A Ticket Routing Recommendation Engine for Enterprise Problem Resolution"Demo Description. In 34th International Conference on Very Large Data Bases (VLDB) / PVLDB Journal, Vol.1, 2008.

Faculty:

            Yi Chen < yi.chen at njit dot edu >

Students:

            Brian Ackerman < bjackerm at asu dot edu >

            Yunzhong Liu < yunzhong dot liu at asu dot edu >

Alumni:

            Peng Sun, Yichuan Cai

Collaborators:

            Shu Tao (IBM T. J. Watson Research Center)