Competitive recommendation systems

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.

[1]  W. Hoeffding.  Probability Inequalities for sums of Bounded Random Variables , 1963 .

[2]  J. Bettman.  An information processing theory of consumer choice , 1979 .

[3]  János Komlós,et al.  The eigenvalues of random symmetric matrices , 1981, Comb..

[4]  Gene H. Golub,et al.  Matrix computations , 1983 .

[5]  Leslie G. Valiant,et al.  A theory of the learnable , 1984, CACM.

[6]  Béla Bollobás,et al.  Random Graphs , 1985 .

[7]  Ravi B. Boppana,et al.  Eigenvalues and graph bisection: An average-case analysis , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).

[8]  Johanna D. Moore,et al.  Proceedings of the Conference on Human Factors in Computing Systems , 1989 .

[9]  J. Howard.  Consumer Behavior In Marketing Strategy , 1989 .

[10]  Robert B. Allen,et al.  User Models: Theory, Method, and Practice , 1990, Int. J. Man Mach. Stud..

[11]  T. Landauer,et al.  Indexing by Latent Semantic Analysis , 1990 .

[12]  Rashi Glazer.  Marketing in an Information-Intensive Environment: Strategic Implications of Knowledge as an Asset , 1991 .

[13]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[14]  Upendra Shardanand.  Social information filtering for music recommendation , 1994 .

[15]  N. Fisher,et al.  Probability Inequalities for Sums of Bounded Random Variables , 1994 .

[16]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[17]  John D. C. Little,et al.  The Marketing Information Revolution , 1994 .

[18]  Susan T. Dumais,et al.  Using Linear Algebra for Intelligent Information Retrieval , 1995, SIAM Rev..

[19]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

[20]  Mark Rosenstein,et al.  Recommending and evaluating choices in a virtual community of use , 1995, CHI '95.

[21]  Dennis L. Hoffman,et al.  Marketing in Hypermedia Computer-Mediated Environments : Conceptual Foundations 1 ) , 1998 .

[22]  Bradley N. Miller,et al.  Experiences with GroupLens: marking usenet useful again , 1997 .

[23]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[24]  Ravi Kumar,et al.  Recommendation systems: a probabilistic analysis , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).

[25]  Santosh S. Vempala,et al.  Latent semantic indexing: a probabilistic analysis , 1998, PODS '98.

[26]  Jon M. Kleinberg,et al.  Segmentation problems , 2004, JACM.

[27]  Alan M. Frieze,et al.  Fast Monte-Carlo algorithms for finding low-rank approximations , 1998, Proceedings 39th Annual Symposium on Foundations of Computer Science (Cat. No.98CB36280).

[28]  Alan M. Frieze,et al.  Clustering in large graphs and matrices , 1999, SODA '99.

[29]  Ravi Kumar,et al.  On targeting Markov segments , 1999, STOC '99.

[30]  A. K. Pujari,et al.  Data Mining Techniques , 2006 .

[31]  Anna R. Karlin,et al.  Spectral analysis of data , 2001, STOC '01.

[32]  Petros Drineas,et al.  Fast Monte-Carlo algorithms for approximate matrix multiplication , 2001, Proceedings 2001 IEEE International Conference on Cluster Computing.

[33]  Dimitris Achlioptas,et al.  Fast computation of low rank matrix approximations , 2001, STOC '01.

[34]  C. Papadimitriou,et al.  On the value of private information , 2001 .

[35]  A. ADoefaa,et al.  ? ? ? ? f ? ? ? ? ? , 2003 .

[36]  Limsoon Wong,et al.  DATA MINING TECHNIQUES , 2003 .

[37]  Petros Drineas,et al.  Pass efficient algorithms for approximating large matrices , 2003, SODA '03.