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Home > Research > Themes > Human-Computer Interaction

Human-Computer Interaction

HCI studies how computer systems can be better designed to support users' need. At SI we study HCI at many different scales and from many different viewpoints. Our research includes studying how people adopt and use technologies as well as building new systems to augment the capabilities of individuals, groups, and communities. Areas of particular interest at SI include social computing, computer-supported cooperative work, collaboratories, information visualization, and pervasive computing. (Also see Technology-Mediated Collaboration)

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research project logoCenter for Information Technology Integration (CITI)
The Center for Information Technology Integration engages in advanced development and research projects, in partnership with external sponsors, that will enhance the University of Michigan's information technology environment; and transfers the results to industry, government, and education. Since 1986, CITI has studied and developed information technologies that enhance the campus computing infrastructure.
Contact: Thomas Finholt (finholt@umich.edu)
Web 2.0 Community Data Mining and Expertise (QuME) Expertise finders are an important class of collaborative recommendation systems, but they suffer from a general problem: Current expertise finders, both commercial and research, cannot infer expertise levels very well. Traditionally, expertise finders have relied on the standard information similarity measures (such as term vector comparisons). The ability to add the level of expertise would be a major step forward for expertise finders, and would likely open up a range of new application possibilities. This work proposes to solve this problem by constructing a prototype middleware system, called QuME, which contains a number of mechanisms to facilitate expertise finding, expertise exchange, and social interaction for online communities and organizations. QuME includes novel mechanisms to infer expertise levels, making a larger range of social interaction possible.
Contact: Mark Ackerman (ackerm@umich.edu)
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