A visual interface for social information filtering
|Title:||A visual interface for social information filtering||Authors:||O'Donovan, John
|Permanent link:||http://hdl.handle.net/10197/1662||Date:||Aug-2009||Abstract:||Collaborative or “Social” filtering has been successfully deployed over the years as a technique for analysing large amounts of user-preference knowledge to predict interesting items for an individual user. The black-box nature of most collaborative filtering (CF) applications leave the user wondering how the system arrived at its recommendation. In this paper we introduce PeerChooser, a collaborative recommender system with an interactive interface which provides the user not only an explanation of the recommendation process, but the opportunity to manipulate a graph of their peers at varying levels of granularity, to reflect aspects of their current requirements. PeerChooser’s prediction component reads directly from the graph to yield the same results as a benchmark recommendation algorithm. Users then improve on these predictions by tweaking the graph in various ways. PeerChooser compares favorably against the benchmark in live evaluations and equally well in automated accuracy tests.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||IEEE Computer Society||Copyright (published version):||2009 by The Institute of Electrical and Electronics Engineers, Inc.||Subject LCSH:||Recommender systems (Information filtering)
|DOI:||10.1109/CSE.2009.26||Language:||en||Status of Item:||Peer reviewed||Is part of:||Proceedings : 12th IEEE International Conference on Computational Science and Engineering : CSE 2009 : Vol. 4||Conference Details:||Paper presented at the 2009 IEEE International Conference on Social Computing (SocialCom 2009) in conjunction with the 2009 IEEE International Conference on Social Computing, 29th - 31st August 2009, Vancouver, Canada|
|Appears in Collections:||CLARITY Research Collection|
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