Keywords
UIST2.0 Archive - 20 years of UIST
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cscw

cscw

In Proceedings of UIST 1992
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TelePICTIVE: computer-supported collaborative GUI design for designers with diverse expertise (p. 151-160)

In Proceedings of UIST 1993
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Animating user interfaces using animation servers (p. 69-79)

In Proceedings of UIST 1993
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The Rendezvous constraint maintenance system (p. 225-234)

In Proceedings of UIST 1994
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Building distributed, multi-user applications by direct manipulation (p. 71-80)

In Proceedings of UIST 1995
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High-latency, low-bandwidth windowing in the Jupiter collaboration system (p. 111-120)

In Proceedings of UIST 1995
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Supporting distributed, concurrent, one-way constraints in user interface applications (p. 121-132)

In Proceedings of UIST 1995
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Social activity indicators: interface components for CSCW systems (p. 159-168)

In Proceedings of UIST 1996
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The VIEP system: interacting with collaborative multimedia (p. 59-66)

In Proceedings of UIST 1997
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Simplifying component development in an integrated groupware environment (p. 65-72)

In Proceedings of UIST 1997
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Flexible conflict detection and management in collaborative applications (p. 139-148)

In Proceedings of UIST 2001
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The designers' outpost: a tangible interface for collaborative web site (p. 1-10)

In Proceedings of UIST 2003
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Rhythm modeling, visualizations and applications (p. 11-20)

In Proceedings of UIST 2003
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Classroom BRIDGE: using collaborative public and desktop timelines to support activity awareness (p. 21-30)

In Proceedings of UIST 2005
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Role-based control of shared application views (p. 23-32)

In Proceedings of UIST 2006
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Multi-user, multi-display interaction with a single-user, single-display geospatial application (p. 273-276)

In Proceedings of UIST 2007
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QuME: a mechanism to support expertise finding in online help-seeking communities (p. 111-114)

Abstract plus

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.