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Emergent properties of referral systems
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
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To solve some difficult problems that requires procedural knowledge, people often seek the advice of experts who have got competence in that problem domain. This paper focuses on locating and determining an expert in a particular knowledge domain. In most cases, social network of a user is explored through referrals to locate human experts. Past work in searching for experts through referrals focused primarily on static social network. However, static social network fail to accurately represent the set of experts, as in a knowledge domain as time evolves experts continuously keep changing. This paper focuses on the problem of finding experts through referrals in a time evolving co-author social network. Authors and co-authors of research publication for instance are domain experts. In this paper, we propose a solution where the network is expanded incrementally and the information on domain experts is suitably modified. This will avoid periodic global expertise recomputation and would help to effectively retrieve relevant information on domain experts. A novel data structure is also introduced in our study to effectively track the change in expertise of an author with time.