Graph Mining for Automatic Classification of Logical Proofs

Karel Vaculík, Luboš Popelínský

2014

Abstract

We introduce graph mining for evaluation of logical proofs constructed by undergraduate students in the introductory course of logic. We start with description of the source data and their transformation into GraphML. As particular tasks may differ—students solve different tasks—we introduce a method for unification of resolution steps that enables to generate generalized frequent subgraphs. We then introduce a new system for graph mining that uses generalized frequent patterns as new attributes. We show that both overall accuracy and precision for incorrect resolution proofs overcome 97%. We also discuss a use of emergent patterns and three-class classification (correct/incorrect/unrecognised).

Paper Citation

in Harvard Style

Vaculík K. and Popelínský L. (2014). Graph Mining for Automatic Classification of Logical Proofs . In Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU, ISBN 978-989-758-020-8, pages 563-568. DOI: 10.5220/0004963405630568

in Bibtex Style

@conference{csedu14,
author={Karel Vaculík and Luboš Popelínský},
title={Graph Mining for Automatic Classification of Logical Proofs},
booktitle={Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU,},
year={2014},
pages={563-568},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004963405630568},
isbn={978-989-758-020-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Computer Supported Education - Volume 1: CSEDU,
TI - Graph Mining for Automatic Classification of Logical Proofs
SN - 978-989-758-020-8
AU - Vaculík K.
AU - Popelínský L.
PY - 2014
SP - 563
EP - 568
DO - 10.5220/0004963405630568