Using data and theory in multistrategy (mis)concept(ion) discovery (1997)
| Venue: | Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence |
| Citations: | 1 - 0 self |
BibTeX
@INPROCEEDINGS{Sison97usingdata,
author = {Raymund Sison and Masayuki Numao and Masamichi Shimura},
title = {Using data and theory in multistrategy (mis)concept(ion) discovery},
booktitle = {Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence},
year = {1997}
}
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Abstract
Most conceptual clustering systems rely solely on data to form concepts without supervision; the few that exploit causalities in the background knowledge do so only after the completion of a similarity-based learning phase. In this paper, we describe a multistrategy misconception discovery system, MMD, that utilizes data and theory in a more tightly coupled way. The integration of similarity- and causality-based learning in MMD is shown to be essential for the automatic construction of accurate and meaningful misconceptions that account for errors in novice behavior. 1
