Manipulation Robustness of Collaborative Filtering Systems

Details Manipulation Robustness of Collaborative Filtering Systems Manipulation Robustness of Collaborative Filtering Systems

2009-02-28

arxiv.org/abs/0903.0064v2

Computer Science

Learning

Scientific paper

A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions, and hence have become targets of manipulation by unscrupulous vendors. We provide theoretical and empirical results demonstrating that while common nearest neighbor algorithms, which are widely used in commercial systems, can be highly susceptible to manipulation, two classes of collaborative filtering algorithms which we refer to as linear and asymptotically linear are relatively robust. These results provide guidance for the design of future collaborative filtering systems.

Affiliated with

Also associated with

No associations

Rating

Manipulation Robustness of Collaborative Filtering Systems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Manipulation Robustness of Collaborative Filtering Systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Manipulation Robustness of Collaborative Filtering Systems will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-48591