User initiated learning for adaptive interfaces

Details

Event IJCAI Workshop on Intelligence and Interaction

Authors

Brdiczka, Oliver
Technical Publications
July 13th 2009
Intelligent user interfaces employ machine learning to learn and adapt according to user peculiarities. In all these cases, the learning tasks are predefined and a machine-learning expert is involved in the development process. This significantly limits the potential utility of machine-learning since there is no way for a user to create new learning tasks for specific needs as they arise. We address this shortcoming by developing a framework for user-initiated learning (UIL), where the end user can define new learning tasks, after which the system automatically generates a learning component, without the intervention of an expert. We describe the knowledge representation and reasoning required to replace the expert, so as to automatically generate labeled training examples, select features, and learn the required concept. We present an implementation of this approach for a popular email client and give initial experimental results.

Citation

Judah, K.; Dietterich, T.; Fern, A.; Irvine, J.; Slater, M.; Tadepalli, P.; Gervasio, M.; Ellwood, C.; Jarrold, B.; Brdiczka, O.; Blythe, J. User initiated learning for adaptive interfaces. IJCAI Workshop on Intelligence and Interaction; 2009 July 13; Pasadena, CA.

Additional information

Focus Areas

Our work is centered around a series of Focus Areas that we believe are the future of science and technology.

FIND OUT MORE
Licensing & Commercialization Opportunities

We’re continually developing new technologies, many of which are available for¬†Commercialization.

FIND OUT MORE
News

PARC scientists and staffers are active members and contributors to the science and technology communities.

FIND OUT MORE