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ISMB
1993
13 years 9 months ago
Knowledge-Based Generation of Machine-Learning Experiments: Learning with DNA Crystallography Data
Thoughit has been possible in the past to learn to predict DNAhydration patterns from crystallographic data, there is ambiguity in the choice of training data (both in terms of th...
Dawn M. Cohen, Casimir A. Kulikowski, Helen Berman
INTETAIN
2005
Springer
14 years 1 months ago
Grounding Emotions in Human-Machine Conversational Systems
In this paper we investigate the role of user emotions in human-machine goal-oriented conversations. There has been a growing interest in predicting emotions from acted and non-act...
Giuseppe Riccardi, Dilek Z. Hakkani-Tür
VL
2010
IEEE
216views Visual Languages» more  VL 2010»
13 years 6 months ago
Explanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a “prog...
Todd Kulesza, Simone Stumpf, Margaret M. Burnett, ...
ICALT
2006
IEEE
14 years 1 months ago
Towards Effective Usage-Based Learning Applications: Track and Learn from User Experience(s)
In this paper we propose a schema and framework for recording and managing attention metadata. This framework is intended to capture, manage, and re-use data about attention users...
Jehad Najjar, Erik Duval, Martin Wolpers
ICALT
2003
IEEE
14 years 1 months ago
Learning Objects on the Semantic Web
This paper presents ABLO, a first-attempt at engineering a more active learning object based on agent technologies that allows more sophisticated kinds of learning object reuse tha...
Permanand Mohan, Christopher A. Brooks