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LWA
2007
13 years 6 months ago
Towards Learning User-Adaptive State Models in a Conversational Recommender System
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Tariq Mahmood, Francesco Ricci
CI
2010
129views more  CI 2010»
13 years 4 months ago
On-Line Case-Based Planning
Some domains, such as real-time strategy (RTS) games, pose several challenges to traditional planning and machine learning techniques. In this paper, we present a novel on-line ca...
Santi Ontañón, Kinshuk Mishra, Neha ...
ECTEL
2007
Springer
13 years 11 months ago
Using MotSaRT to Support On-Line Teachers in Student Motivation
Motivation to learn is affected by a student’s self-efficacy, goal orientation, locus of control and perceived task difficulty. In the classroom, teachers know how to motivate th...
Teresa Hurley, Stephan Weibelzahl
AAAI
2004
13 years 6 months ago
Making Better Recommendations with Online Profiling Agents
In recent years, we have witnessed the success of autonomous agents applying machine learning techniques across a wide range of applications. However, agents applying the same mac...
Danny Oh, Chew Lim Tan
SAC
2005
ACM
13 years 10 months ago
Stochastic scheduling of active support vector learning algorithms
Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
Gaurav Pandey, Himanshu Gupta, Pabitra Mitra