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AAAI
2006
13 years 9 months ago
Computing Slater Rankings Using Similarities among Candidates
Voting (or rank aggregation) is a general method for aggregating the preferences of multiple agents. One important voting rule is the Slater rule. It selects a ranking of the alte...
Vincent Conitzer
CISS
2008
IEEE
14 years 2 months ago
A lower-bound on the number of rankings required in recommender systems using collaborativ filtering
— We consider the situation where users rank items from a given set, and each user ranks only a (small) subset of all items. We assume that users can be classified into C classe...
Peter Marbach
KDD
2001
ACM
150views Data Mining» more  KDD 2001»
14 years 8 months ago
Empirical bayes screening for multi-item associations
This paper considers the framework of the so-called "market basket problem", in which a database of transactions is mined for the occurrence of unusually frequent item s...
William DuMouchel, Daryl Pregibon
SBRN
2008
IEEE
14 years 2 months ago
Selecting Neural Network Forecasting Models Using the Zoomed-Ranking Approach
In this work, we propose to use the Zoomed-Ranking approach to ranking and selecting Artificial Neural Network (ANN) models for time series forecasting. Given a time series to fo...
Patrícia M. Santos, Teresa Bernarda Ludermi...
WWW
2009
ACM
14 years 2 months ago
Tagommenders: connecting users to items through tags
Tagging has emerged as a powerful mechanism that enables users to find, organize, and understand online entities. Recommender systems similarly enable users to efficiently navig...
Shilad Sen, Jesse Vig, John Riedl