A Logic-Based Approach to Mining Inductive Databases
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Liu, Hong-Cheu, Yu, Jeffrey Xu, Zeleznikow, John 
ORCID: 0000-0002-8786-2644 and Guan, Ying
(2007)
A Logic-Based Approach to Mining Inductive Databases.
In:
Computational Science ICCS 2007: 7th International Conference, Beijing, China, May 27 - 30, 2007, Proceedings.
Shi, Yong, van Albada, Geert Dick, Dongarra, Jack and Sloot, Peter M. A, eds.
Lecture Notes in Computer Science , 1
(4487).
Springer, Berlin, Germany, pp. 270-277.
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.
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| Item type | Book Section |
| URI | https://vuir.vu.edu.au/id/eprint/10693 |
| DOI | 10.1007/978-3-540-72584-8_35 |
| Official URL | http://download.springer.com/static/pdf/168/chp%25... |
| ISBN | 9783540725831 |
| Subjects | Historical > RFCD Classification > 280000 Information, Computing and Communication Sciences Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing Historical > FOR Classification > 0806 Information Systems Historical > Faculty/School/Research Centre/Department > School of Management and Information Systems Historical > SEO Classification > 8999 Other Information and Communication Services |
| Keywords | ResPubID13939, relational computation, association rule mining, fixpoint computation, logic-based inductive query language, data mining query language design, inductive database system |
| Citations in Scopus | 3 - View on Scopus |
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