Name
Abstract | ||
|---|---|---|
A recommendation system tracks past purchases of a group of users to make product recommendations to individual members of the group. In this paper we present a notion of competitive recommendation systems, building on recent theoretical work on this subject. We reduce the problem of achieving competitiveness to a problem in matrix reconstruction. We then present a matrix reconstruction scheme that is competitive: it requires a small overhead in the number of users and products to be sampled, delivering in the process a net utility that closely approximates the best possible with full knowledge of all user-product preferences. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1145/509907.509922 | STOC |
Keywords | Field | DocType |
past purchase,individual member,recommendation system,matrix reconstruction scheme,product recommendation,recent theoretical work,small overhead,full knowledge,matrix reconstruction,competitive recommendation system,treewidth,recommender system | Recommender system,Discrete mathematics,Mathematical optimization,Combinatorics,Matrix (mathematics),Computer science,Treewidth | Conference |
ISBN | Citations | PageRank |
1-58113-495-9 | 55 | 6.50 |
References | Authors | |
16 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Petros Drineas | 1 | 2165 | 201.55 |
| Iordanis Kerenidis | 2 | 291 | 30.58 |
| Prabhakar Raghavan | 3 | 13351 | 2776.61 |