%0 Conference Paper %1 citeulike:2813437 %A Zhang, Jun %A Ackerman, Mark S. %A Adamic, Lada %A Nam, Kevin K. %B UIST '07: Proceedings of the 20th annual ACM symposium on User interface software and technology %C New York, NY, USA %D 2007 %I ACM %K expert-finding social-network %P 111--114 %R 10.1145/1294211.1294230 %T QuME: a mechanism to support expertise finding in online help-seeking communities %U http://dx.doi.org/10.1145/1294211.1294230 %X 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. %@ 978-1-59593-679-2

@inproceedings{citeulike:2813437, 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.}, added-at = {2009-07-01T11:12:30.000+0200}, address = {New York, NY, USA}, author = {Zhang, Jun and Ackerman, Mark S. and Adamic, Lada and Nam, Kevin K.}, biburl = {https://www.bibsonomy.org/bibtex/2cdd420f2aaff4bfcdff44bdc2a9dc0da/brusilovsky}, booktitle = {UIST '07: Proceedings of the 20th annual ACM symposium on User interface software and technology}, citeulike-article-id = {2813437}, doi = {10.1145/1294211.1294230}, interhash = {5c1b228ef26ed62e9213f08c758742e0}, intrahash = {cdd420f2aaff4bfcdff44bdc2a9dc0da}, isbn = {978-1-59593-679-2}, keywords = {expert-finding social-network}, location = {Newport, Rhode Island, USA}, pages = {111--114}, posted-at = {2009-06-30 10:38:42}, priority = {2}, publisher = {ACM}, timestamp = {2009-07-01T11:12:31.000+0200}, title = {QuME: a mechanism to support expertise finding in online help-seeking communities}, url = {http://dx.doi.org/10.1145/1294211.1294230}, year = 2007 }