An Enhanced Block Notation for Discrimination Network Optimisation

Christoph Terwelp, Karl-Heinz Krempels, Fabian Ohler

2016

Abstract

Because of their ability to efficiently store, access, and process data, Database Management Systems (DBMSs) and Rule-based Systems (RBSs) are used in many information systems as information processing units. A basic function of a RBS and a function of many DBMSs is to match conditions on the available data. To improve performance, intermediate results are stored in Discrimination Networks (DNs). The resulting memory consumption and runtime cost depend on the structure of the DN. A lot of research has been done in the area of optimising DNs. In this paper, we focus on re-using network parts considering multiple rule conditions and exploiting the characteristics of equivalences. Hence, we present an approach incorporating the potential of both concepts as an enhancement to previous work.

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Paper Citation


in Harvard Style

Terwelp C., Krempels K. and Ohler F. (2016). An Enhanced Block Notation for Discrimination Network Optimisation . In Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST, ISBN 978-989-758-186-1, pages 268-273. DOI: 10.5220/0005905302680273

in Bibtex Style

@conference{webist16,
author={Christoph Terwelp and Karl-Heinz Krempels and Fabian Ohler},
title={An Enhanced Block Notation for Discrimination Network Optimisation},
booktitle={Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,},
year={2016},
pages={268-273},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005905302680273},
isbn={978-989-758-186-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,
TI - An Enhanced Block Notation for Discrimination Network Optimisation
SN - 978-989-758-186-1
AU - Terwelp C.
AU - Krempels K.
AU - Ohler F.
PY - 2016
SP - 268
EP - 273
DO - 10.5220/0005905302680273