A new hybrid architecture for the discovery and compaction of knowledge : breast cancer datasets case study
Joint Authors
Awdah, Muhammad
Kharbat, Fatin
Bull, Larry
Source
The International Arab Journal of Information Technology
Issue
Vol. 11, Issue 2 (31 Mar. 2014)9 p.
Publisher
Publication Date
2014-03-31
Country of Publication
Jordan
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
This paper reports on the development of a new hybrid architecture that integrates Learning Classifier Systems (LCS) with Rete-based Production Systems Inference Engine to improve the performance of the process of compacting LCS generated rules.
While LCS is responsible for generating a complete rule set from a given breast cancer pathological data-set, an adapted Rete-based inference engine has been integrated for the efficient extraction of a minimal and representative rule set from the original generated rule set.
This has resulted in an architecture that is hybrid, efficient, component-based, elegant and extensible.
Also, this has demonstrated significant savings in computing the match phase when building on the two main features of the Rete match algorithm, namely structural similarity and temporal redundancy.
Finally, this architecture may be considered as a new platform for research on compaction of LCS rules using Rete-based inference engines.
American Psychological Association (APA)
Kharbat, Fatin& Awdah, Muhammad& Bull, Larry. 2014. A new hybrid architecture for the discovery and compaction of knowledge : breast cancer datasets case study. The International Arab Journal of Information Technology،Vol. 11, no. 2.
https://search.emarefa.net/detail/BIM-334238
Modern Language Association (MLA)
Kharbat, Fatin…[et al.]. A new hybrid architecture for the discovery and compaction of knowledge : breast cancer datasets case study. The International Arab Journal of Information Technology Vol. 11, no. 2 (Mar. 2014).
https://search.emarefa.net/detail/BIM-334238
American Medical Association (AMA)
Kharbat, Fatin& Awdah, Muhammad& Bull, Larry. A new hybrid architecture for the discovery and compaction of knowledge : breast cancer datasets case study. The International Arab Journal of Information Technology. 2014. Vol. 11, no. 2.
https://search.emarefa.net/detail/BIM-334238
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-334238