Enhancing the Efficiency of a Decision Support System through the Clustering of Complex Rule-Based Knowledge Bases and Modification of the Inference Algorithm
Author
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-06
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Decision support systems founded on rule-based knowledge representation should be equipped with rule management mechanisms.
Effective exploration of new knowledge in every domain of human life requires new algorithms of knowledge organization and a thorough search of the created data structures.
In this work, the author introduces an optimization of both the knowledge base structure and the inference algorithm.
Hence, a new, hierarchically organized knowledge base structure is proposed as it draws on the cluster analysis method and a new forward-chaining inference algorithm which searches only the so-called representatives of rule clusters.
Making use of the similarity approach, the algorithm tries to discover new facts (new knowledge) from rules and facts already known.
The author defines and analyses four various representative generation methods for rule clusters.
Experimental results contain the analysis of the impact of the proposed methods on the efficiency of a decision support system with such knowledge representation.
In order to do this, four representative generation methods and various types of clustering parameters (similarity measure, clustering methods, etc.) were examined.
As can be seen, the proposed modification of both the structure of knowledge base and the inference algorithm has yielded satisfactory results.
American Psychological Association (APA)
Nowak-Brzezińska, Agnieszka. 2018. Enhancing the Efficiency of a Decision Support System through the Clustering of Complex Rule-Based Knowledge Bases and Modification of the Inference Algorithm. Complexity،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1133124
Modern Language Association (MLA)
Nowak-Brzezińska, Agnieszka. Enhancing the Efficiency of a Decision Support System through the Clustering of Complex Rule-Based Knowledge Bases and Modification of the Inference Algorithm. Complexity No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1133124
American Medical Association (AMA)
Nowak-Brzezińska, Agnieszka. Enhancing the Efficiency of a Decision Support System through the Clustering of Complex Rule-Based Knowledge Bases and Modification of the Inference Algorithm. Complexity. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1133124
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133124