Measuring and Improving the Effectiveness of Representations
Proceedings of the Twelfth International Joint Conference on Artificial Intelligence. Knowledge Representation. Pages 518-523.
Abstract
This report discusses what it means to claim that a representation is an effective encoding of knowledge. We first present dimensions of merit for evaluating representations, based on the view that usefulness is a behavioral property, and is necessarily relative to a specified task. We then provide methods (based on results from mathematical statistics) for reliably measuring effectiveness empirically, and hence for comparing different representations. We also discuss weak but guaranteed methods of improving inadequate representations. Our results are an application of the ideas of formal learning theory to concrete knowledge representation formalisms.
@inproceedings{ijcai1991p78,
title = {Measuring and Improving the Effectiveness of Representations},
author = {Greiner, Russell and Elkan, Charles},
booktitle = {Proceedings of the Twelfth International Joint Conference on
Artificial Intelligence, {IJCAI-91}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John Mylopoulos and Ray Reiter},
pages = {518--523},
year = {1991},
month = {8},
note = {Knowledge Representation},
url = {https://ijcai.org/proceedings/1991/78},
}
TY - CPAPER TI - Measuring and Improving the Effectiveness of Representations AU - Greiner, Russell AU - Elkan, Charles T2 - Proceedings of the Twelfth International Joint Conference on Artificial Intelligence, IJCAI-91 PB - International Joint Conferences on Artificial Intelligence PY - 1991 SP - 518 EP - 523 UR - https://ijcai.org/proceedings/1991/78 ER -Copied
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