Evaluating Rank Accuracy based on Incomplete Pairwise Preferences

  title={Evaluating Rank Accuracy based on Incomplete Pairwise Preferences},
  author={Brian Ackerman},
Existing methods to measure the rank accuracy of a recommender system assume the ground truth is either a set of user ratings or a total ordered list of items given by the user with possible ties. However, in many applications we are only able to obtain implicit user feedback, which does not provide such comprehensive information, but only gives a set of pairwise preferences among items. Generally such pairwise preferences are not complete, and thus may not deduce a total order of items. In… CONTINUE READING

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