THE INFERENCE EFFICIENCY PROBLEM IN BUSINESS AND TECHNOLOGICAL RULES MANAGEMENT SYSTEMS

Barbara Baster, Andrzej Macioł

Abstract

In the following paper we present the results of our works related to development of rule engine for automated interpretation of business rules. Our experiences and experimental results show that knowledge description for this purpose may be stored in the form of relational databases. The aim of the experimental research presented in this paper was to determine degree in which organization of knowledge base and assumed inference strategy influence the efficiency of inference process itself. Experiments proved that owing to the application of mechanism characteristic for relational data bases, knowledge base can be easily arranged so as to maximize efficiency of inference. The efficiency of inference is strongly influenced by preliminary knowledge transformation from the set of examples or random rules into arranged form.

References

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Paper Citation


in Harvard Style

Baster B. and Macioł A. (2010). THE INFERENCE EFFICIENCY PROBLEM IN BUSINESS AND TECHNOLOGICAL RULES MANAGEMENT SYSTEMS . In Proceedings of the 5th International Conference on Software and Data Technologies - Volume 1: ICSOFT, ISBN 978-989-8425-22-5, pages 10-15. DOI: 10.5220/0002931600100015


in Bibtex Style

@conference{icsoft10,
author={Barbara Baster and Andrzej Macioł},
title={THE INFERENCE EFFICIENCY PROBLEM IN BUSINESS AND TECHNOLOGICAL RULES MANAGEMENT SYSTEMS},
booktitle={Proceedings of the 5th International Conference on Software and Data Technologies - Volume 1: ICSOFT,},
year={2010},
pages={10-15},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002931600100015},
isbn={978-989-8425-22-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Software and Data Technologies - Volume 1: ICSOFT,
TI - THE INFERENCE EFFICIENCY PROBLEM IN BUSINESS AND TECHNOLOGICAL RULES MANAGEMENT SYSTEMS
SN - 978-989-8425-22-5
AU - Baster B.
AU - Macioł A.
PY - 2010
SP - 10
EP - 15
DO - 10.5220/0002931600100015