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u-Help: supporting helpful communities with information technology

Published:06 May 2013Publication History

ABSTRACT

When people need help with day-to-day tasks they turn to family, friends or neighbours to help them out. Despite an increasingly networked world, technology falls short in supporting such daily tasks. u-Help provides a platform for building a community of helpful people and supports them in finding volunteers for day-to-day tasks. It relies on three techniques that allow a requester and volunteer to find one another easily, and build up a community around such provision of services. First, we use an ontology to distinguish between the various tasks that u-Help allows people to provide. Second, a computational trust model is used to aggregate feedback from community members and allows people to discover who are good or bad at performing the various tasks. Last, a flooding algorithm quickly disseminates requests for help through the community.

References

  1. Y. Li, Z. A. Bandar, and D. McLean. An approach for measuring semantic similarity between words using multiple information sources. IEEE Transactions on Knowledge and Data Engineering, 15(4):871--881, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. N. Osman, C. Sierra, and J. Sabater-Mir. Propagation of opinions in structural graphs. In Proc. of ECAI 2010, volume 215 of Frontiers in AI and Applications, pages 595--600. IOS Press, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. u-Help: supporting helpful communities with information technology

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    • Published in

      cover image ACM Other conferences
      AAMAS '13: Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
      May 2013
      1500 pages
      ISBN:9781450319935

      Publisher

      International Foundation for Autonomous Agents and Multiagent Systems

      Richland, SC

      Publication History

      • Published: 6 May 2013

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      • poster

      Acceptance Rates

      AAMAS '13 Paper Acceptance Rate140of599submissions,23%Overall Acceptance Rate1,155of5,036submissions,23%

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