QuME: A Mechanism to Support Expertise Finding in Online Help-seeking Communities

Publication Type:

Conference Paper

Source:

Proceedings of the ACM Symposium on User Interface Systems and Technology (UIST'07), p.111-114 (2007)

URL:

http://www.eecs.umich.edu/~ackerm/pub/07b43/zhangackermanadamicnam.uist07.final-a.pdf

Keywords:

expertise finding, expertise location, online communities, QuME, social computing

Abstract:

Help-seeking communities have been playing an increasingly critical role in the way people seek and share information. However, traditional help-seeking mechanisms of these online communities have some limitations. In this paper, we describe an expertise-finding mechanism that attempts to alleviate the limitations caused by not knowing users’ expertise levels. As a result of using social network data from the online community, this mechanism can automatically infer expertise level. This allows, for example, a question list to be personalized to the user's expertise level as well as to keyword similarity. We believe this expertise location mechanism will facilitate the development of next generation help-seeking communities