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» Relevance Feedback Models for Recommendation
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CHI
2010
ACM
14 years 3 months ago
Short and tweet: experiments on recommending content from information streams
More and more web users keep up with newest information through information streams such as the popular microblogging website Twitter. In this paper we studied content recommendat...
Jilin Chen, Rowan Nairn, Les Nelson, Michael Berns...
ICASSP
2009
IEEE
14 years 3 months ago
Exploiting user feedback for language model adaptation in meeting recognition
We investigate language model (LM) adaptation in a meeting recognition application, where the LM is adapted based on recognition output from relevant prior meetings and partial ma...
Dimitra Vergyri, Andreas Stolcke, Gökhan T&uu...
SIGIR
2006
ACM
14 years 2 months ago
Learning user interaction models for predicting web search result preferences
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
ICDM
2010
IEEE
172views Data Mining» more  ICDM 2010»
13 years 6 months ago
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations
Cold-start scenarios in recommender systems are situations in which no prior events, like ratings or clicks, are known for certain users or items. To compute predictions in such ca...
Zeno Gantner, Lucas Drumond, Christoph Freudenthal...
KDD
2004
ACM
150views Data Mining» more  KDD 2004»
14 years 9 months ago
Complete This Puzzle: A Connectionist Approach to Accurate Web Recommendations Based on a Committee of Predictors
Abstract. We present a Context Ultra-Sensitive Approach based on two-step Recommender systems (CUSA-2step-Rec). Our approach relies on a committee of profile-specific neural networ...
Olfa Nasraoui, Mrudula Pavuluri