Recommenders everywhere:: the WikiLens community-maintained recommender system

Authors:
Dan Frankowski;Shyong K. Lam;Shilad Sen;F. Maxwell Harper;Scott Yilek;Michael Cassano;John Riedl
Affiliations:
University of Minnesota, Minneapolis, MN;University of Minnesota, Minneapolis, MN;University of Minnesota, Minneapolis, MN;University of Minnesota, Minneapolis, MN;University of Minnesota, Minneapolis, MN;University of Minnesota, Minneapolis, MN;University of Minnesota, Minneapolis, MN
Venue:
Proceedings of the 2007 international symposium on Wikis
Year:
2007

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Abstract

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.