'Masterful' matchmaking in service transactions: Inferred abilities, needs and interests versus activity histories

Hyunggu Jung, Victoria Bellotti, Afsaneh Doryab, Dean Leitersdorf, Jiawei Chen, Benjamin V. Hanrahan, Sooyeon Lee, Dan Turner, Anind K. Dey, John M. Carroll

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

Timebanking is a growing type of peer-to-peer service exchange, but is hampered by the effort of finding good transaction partners. We seek to reduce this effort by using a Matching Algorithm for Service Transactions (MAST). MAST matches transaction partners in terms of similarity of interests and complementarity of abilities and needs. We present an experiment involving data and participants from a real timebanking network, that evaluates the acceptability of MAST, and shows that such an algorithm can retrieve matches that are subjectively better than matches based on matching the category of people's historical offers or requests to the category of a current transaction request.

Original languageEnglish (US)
Title of host publicationCHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
Pages1644-1655
Number of pages12
ISBN (Electronic)9781450333627
DOIs
StatePublished - May 7 2016
Event34th Annual Conference on Human Factors in Computing Systems, CHI 2016 - San Jose, United States
Duration: May 7 2016May 12 2016

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other34th Annual Conference on Human Factors in Computing Systems, CHI 2016
CountryUnited States
CitySan Jose
Period5/7/165/12/16

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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    Jung, H., Bellotti, V., Doryab, A., Leitersdorf, D., Chen, J., Hanrahan, B. V., Lee, S., Turner, D., Dey, A. K., & Carroll, J. M. (2016). 'Masterful' matchmaking in service transactions: Inferred abilities, needs and interests versus activity histories. In CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems (pp. 1644-1655). (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/2858036.2858263