Learning topic models--going beyond SVD
Topic Modeling is an approach used for automatic comprehension and classification of data
in a variety of settings, and perhaps the canonical application is in uncovering thematic …
in a variety of settings, and perhaps the canonical application is in uncovering thematic …
Multi-criteria recommender systems
G Adomavicius, N Manouselis, YO Kwon - Recommender systems …, 2010 - Springer
This chapter aims to provide an overview of the class of multi-criteria recommender systems.
First, it defines the recommendation problem as a multicriteria decision making (MCDM) …
First, it defines the recommendation problem as a multicriteria decision making (MCDM) …
Robust incentive techniques for peer-to-peer networks
Lack of cooperation (free riding) is one of the key problems that confronts today's P2P
systems. What makes this problem particularly difficult is the unique set of challenges that …
systems. What makes this problem particularly difficult is the unique set of challenges that …
A random walk method for alleviating the sparsity problem in collaborative filtering
H Yildirim, MS Krishnamoorthy - … of the 2008 ACM conference on …, 2008 - dl.acm.org
Collaborative Filtering is one of the most widely used approaches in recommendation
systems which predicts user preferences by learning past user-item relationships. In recent …
systems which predicts user preferences by learning past user-item relationships. In recent …
Analysis and classification of multi-criteria recommender systems
N Manouselis, C Costopoulou - World Wide Web, 2007 - Springer
Recent studies have indicated that the application of Multi-Criteria Decision Making (MCDM)
methods in recommender systems has yet to be systematically explored. This observation …
methods in recommender systems has yet to be systematically explored. This observation …
Blind regression: Nonparametric regression for latent variable models via collaborative filtering
We introduce the framework of {\em blind regression} motivated by {\em matrix completion}
for recommendation systems: given $ m $ users, $ n $ movies, and a subset of user-movie …
for recommendation systems: given $ m $ users, $ n $ movies, and a subset of user-movie …
Learning topic models: Identifiability and finite-sample analysis
Topic models provide a useful text-mining tool for learning, extracting, and discovering latent
structures in large text corpora. Although a plethora of methods have been proposed for …
structures in large text corpora. Although a plethora of methods have been proposed for …
Using mixture models for collaborative filtering
J Kleinberg, M Sandler - Journal of Computer and System Sciences, 2008 - Elsevier
A collaborative filtering system at an e-commerce site or similar service uses data about
aggregate user behavior to make recommendations tailored to specific user interests. We …
aggregate user behavior to make recommendations tailored to specific user interests. We …
Using mixture models for collaborative filtering
J Kleinberg, M Sandler - Proceedings of the thirty-sixth annual ACM …, 2004 - dl.acm.org
A collaborative filtering system at an e-commerce site or similar service uses data about
aggregate user behavior to make recommendations tailored to specific user interests. We …
aggregate user behavior to make recommendations tailored to specific user interests. We …
Adaptive matching for expert systems with uncertain task types
V Shah, L Gulikers, L Massoulié… - Operations …, 2020 - pubsonline.informs.org
A matching in a two-sided market often incurs an externality: a matched resource may
become unavailable to the other side of the market, at least for a while. This is especially an …
become unavailable to the other side of the market, at least for a while. This is especially an …