On bootstrapping recommender systems

9 years 5 months ago
On bootstrapping recommender systems
Recommender systems perform much better on users for which they have more information. This gives rise to a problem of satisfying users new to a system. The problem is even more acute considering that some of these hard to profile new users judge the unfamiliar system by its ability to immediately provide them with satisfying recommendations, and may be the quickest to abandon the system when disappointed. Rapid profiling of new users is often achieved through a bootstrapping process - a kind of an initial interview - that elicits users to provide their opinions on certain carefully chosen items or categories. This work offers a new bootstrapping method, which is based on a concrete optimization goal, thereby handily outperforming known approaches in our tests. Categories and Subject Descriptors H.2.8 [Database Management]: Database Applications--Data Mining General Terms Algorithms Keywords collaborative filtering, new user, recommender systems, user cold start
Nadav Golbandi, Yehuda Koren, Ronny Lempel
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2010
Where CIKM
Authors Nadav Golbandi, Yehuda Koren, Ronny Lempel
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