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Authors: Alexander Wöehrer 1 ; Yan Zhang 2 ; Ehtesam-ul-Haq Dar 1 and Peter Brezany 1

Affiliations: 1 University of Vienna, Austria ; 2 University of Vienna;Beijing Jiaotong University, China

ISBN: 978-989-674-011-5

Keyword(s): Data mining operators, Macro optimization, Distributed data mining.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Foundations of Knowledge Discovery in Databases ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: Data mining deals with finding hidden knowledge patterns in often huge data sets. The work presented in this paper elaborates on defining data mining tasks in terms of fine-grained composable operators instead of coarse-grained black box algorithms. Data mining tasks in the knowledge discovery process typically need one relational table as input and data preprocessing and integration beforehand. The possible combination of different kind of operators (relational, data mining and data preprocessing operators) represents a novel holistic view on the knowledge discovery process. Initially, as described in this paper, for the low-level execution phase but yielding the potential for rich optimization similar to relational query optimization. We argue that such macro-optimization embracing the overall KDD process leads to improved performance instead of focusing on just a small part of it via micro-optimization.

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Paper citation in several formats:
Wöehrer A.; Zhang Y.; Dar E.; Brezany P. and (2009). UNBOXING DATA MINING VIA DECOMPOSITION IN OPERATORS - Towards Macro Optimization and Distribution.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009) ISBN 978-989-674-011-5, pages 243-248. DOI: 10.5220/0002333102430248

@conference{kdir09,
author={Alexander Wöehrer and Yan Zhang and Ehtesam{-}ul{-}Haq Dar and Peter Brezany},
title={UNBOXING DATA MINING VIA DECOMPOSITION IN OPERATORS - Towards Macro Optimization and Distribution},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)},
year={2009},
pages={243-248},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002333102430248},
isbn={978-989-674-011-5},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)
TI - UNBOXING DATA MINING VIA DECOMPOSITION IN OPERATORS - Towards Macro Optimization and Distribution
SN - 978-989-674-011-5
AU - Wöehrer, A.
AU - Zhang, Y.
AU - Dar, E.
AU - Brezany, P.
PY - 2009
SP - 243
EP - 248
DO - 10.5220/0002333102430248

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