A Logic-Based Approach to Mining Inductive Databases

Authors:
Hong-Cheu Liu;Jeffrey Xu Yu;John Zeleznikow;Ying Guan
Affiliations:
Department of Computer Science and Information Engineering, Diwan University, Taiwan;Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, China;School of Information Systems, Victoria University, Australia;School of Information Technology and Computer Science, University of Wollongong, Australia
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Year:
2007

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Abstract

In this paper, we discuss the main problems of inductive query languages and optimisation issues. We present a logic-based inductive query language and illustrate the use of aggregates and exploit a new join operator to model specific data mining tasks. We show how a fixpoint operator works for association rule mining and a clustering method. A preliminary experimental result shows that fixpoint operator outperforms SQL and Apriori methods. The results of our framework could be useful for inductive query language design in the development of inductive database systems.