Communications of the ACM
Competitive recommendation systems
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Recommendation Systems: A Probabilistic Analysis
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
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We consider the problem of estimating an individual's product preferences for substitute goods or services. The preferences are elicited by questionnaires that pose a few choice tasks to individuals from the population (respondents). The simplest choice task is a pairwise comparison. To elicit a respondent's ranking of nproducts completely 茂戮驴(nlogn) pairwise comparisons are necessary. These are easily too many in settings where the incentive for the respondent is not high though he might be willing to answer a few questions truthfully. One approach to cope with this complexity is to aggregate the answers of several respondents in order to estimate an individual's complete preference ranking. Here we describe such an aggregation mechanism based on spectral clustering and prove its validity in statistical model of population and respondents.