---
title: "Using Data and Theory in Multistretegy (Mis)Concept(ion) Discovery"
authors:
  - "Rayond Sison"
  - "Masayuki Numao"
  - "Masamichi Shimura"
doi: ""
url: "https://ijcai.org/proceedings/1997/41"
pdf: "https://ijcai.org/proceedings/1997/0041.pdf"
venue: "Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence"
year: 1997
pages: "274-278"
track: "Cognitive Modeling"
keywords:
---

# Using Data and Theory in Multistretegy (Mis)Concept(ion) Discovery

Rayond Sison, Masayuki Numao, Masamichi Shimura

*Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence*, pages 274-278.

## 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 miconception 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.