Google Tech Talks
November, 13 2007
Suppose you have a passion for items of a certain type, and you wish to start a recommender system around those items. You want a system like Amazon or Epinions, but for cookie recipes, local theater, or microbrew beer. How can you set up your recommender system without assembling complicated algorithms, large software infrastructure, a large community of contributors, or even a full catalog of items?
WikiLens is open source software that enables anyone, anywhere to start a community-maintained recommender around any type of item. We introduce five principles for community-maintained recommenders that address the two
key issues: (1) community contribution of items and associated information; and (2) finding items of interest. Since all recommender communities start small, we look at feasibility and utility in the small world, one with few users, few items, few ratings. We describe the features of WikiLens, which are based on our principles, and give lessons learned from two years of experience running
wikilens.org.
Slides at http://www.cs.umn.edu/~dfrankow/files/wikilens12.ppt
Speaker: Dan Frankowski
Dan Frankowski is both computer science researcher and practitioner in software and algorithms development. He got his master's degree in computer science from the University of Minnesota in 1993, then spent a year in Budapest on a Fulbright grant studying mathematics. From 1997 to 2003 he was an algorithms guy at Net Perceptions. From 2003 to 2006 he was a research fellow with the GroupLens research group at the Unviersity of Minnesota, which is most well-known for recommenders, but now studies online community more broadly. He now works as a software engineer for Google Groups.
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