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Tell Me Who I Am: An Interactive Recommendation System

Summary: Tell Me Who I Am:
An Interactive Recommendation System
Noga Alon
Tel Aviv U. and IAS
Baruch Awerbuch
Johns Hopkins U.
Yossi Azar
Tel Aviv U.
Boaz Patt-Shamir§
Tel Aviv U.
January 9, 2008
We consider a model of recommendation systems, where each member from a given set of players
has a binary preference to each element in a given set of objects: intuitively, each player either likes
or dislikes each object. However, the players do not know their preferences. To find his preference
of an object, a player may probe it, but each probe incurs unit cost. The goal of the players is
to learn their complete preference vector (approximately) while incurring minimal cost. This is
possible if many players have similar preference vectors: such a set of players with similar "taste"
may split the cost of probing all objects among them, and share the results of their probes by
posting them on a public billboard. The problem is that players do not know a priori whose taste is


Source: Alon, Noga - School of Mathematical Sciences, Tel Aviv University


Collections: Mathematics