A self evolutionary rule-base

A.M.  Khattak; Z. Pervez; W.A.  Khan; S.Y Lee; Y.K. Lee

doi:10.1007/978-3-642-27210-3_1

A self evolutionary rule-base

A.M. Khattak
, Z. Pervez
, W.A. Khan
, S.Y Lee
, Y.K. Lee

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

The rapid growth in domain knowledge is the main reason for the evolution of knowledgebase’s maintaining the domain knowledge. Rule-based Decision Support Systems (DSS) are the most effected systems with the growing knowledge. The experts need to continuously update the rule-base for the new knowledge. This manual and periodic updates in rule-base are time consuming and less useful. In this paper we propose a Self Evolutionary Rule-base algorithm for rule-bases of DSS to decrease the burden from experts and also provide updated knowledge on time. To achieve this objective, we develop a generic structure for rules storage that not only provide efficient manipulation of rules but a generic structure for storage of rules regardless of rules nature/format. The detail working of proposed Rule-base system for rules storage and manipulation is provided in this paper. For the proof of concept, we have implemented the Self Evolutionary Rule-base algorithm in Socially Interactive Clinical Decision Support System (SI-CDSS). The focus is on diabetes disease patients and the overall SI-CDSS is deployed in Microsoft Azure environment. In its implementation, Rough Set generated rules are used and the algorithm is executed on Rough Set generated rules.

Original language	English
Title of host publication	U-and E-Service, Science and Technology
Editors	Tai-hoon Kim, Hojjat Adeli, Jianhua Ma, Wai-chi Fang, Byeong-Ho Kang, Byungjoo Park, Frode Eika Sandnes, Kun Chang Lee
Publisher	Springer-Verlag
Pages	1-9
Number of pages	9
Volume	264
ISBN (Electronic)	9783642272103
ISBN (Print)	9783642272097
DOIs	https://doi.org/10.1007/978-3-642-27210-3_1
Publication status	Published - 2011
Externally published	Yes
Event	UNESST: International Conference on U- and E-Service, Science and Technology - Jeju Island Duration: 8 Dec 2011 → 10 Dec 2011

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer

Conference

Conference	UNESST: International Conference on U- and E-Service, Science and Technology
Abbreviated title	UNESST
City	Jeju Island
Period	8/12/11 → 10/12/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Rules
Rule-Base
Decision Support System
Algorithms
Performance
Verification

Access to Document

10.1007/978-3-642-27210-3_1

Cite this

Khattak, A. M., Pervez, Z., Khan, W. A., Lee, S. Y., & Lee, Y. K. (2011). A self evolutionary rule-base. In T. Kim, H. Adeli, J. Ma, W. Fang, B.-H. Kang, B. Park, F. E. Sandnes, & K. C. Lee (Eds.), U-and E-Service, Science and Technology (Vol. 264, pp. 1-9). (Communications in Computer and Information Science). Springer-Verlag. https://doi.org/10.1007/978-3-642-27210-3_1

@inproceedings{4e561d391aad4779a41c55a623dc4e68,

title = "A self evolutionary rule-base",

abstract = "The rapid growth in domain knowledge is the main reason for the evolution of knowledgebase{\textquoteright}s maintaining the domain knowledge. Rule-based Decision Support Systems (DSS) are the most effected systems with the growing knowledge. The experts need to continuously update the rule-base for the new knowledge. This manual and periodic updates in rule-base are time consuming and less useful. In this paper we propose a Self Evolutionary Rule-base algorithm for rule-bases of DSS to decrease the burden from experts and also provide updated knowledge on time. To achieve this objective, we develop a generic structure for rules storage that not only provide efficient manipulation of rules but a generic structure for storage of rules regardless of rules nature/format. The detail working of proposed Rule-base system for rules storage and manipulation is provided in this paper. For the proof of concept, we have implemented the Self Evolutionary Rule-base algorithm in Socially Interactive Clinical Decision Support System (SI-CDSS). The focus is on diabetes disease patients and the overall SI-CDSS is deployed in Microsoft Azure environment. In its implementation, Rough Set generated rules are used and the algorithm is executed on Rough Set generated rules.",

keywords = "Rules, Rule-Base, Decision Support System, Algorithms, Performance, Verification",

author = "A.M. Khattak and Z. Pervez and W.A. Khan and S.Y Lee and Y.K. Lee",

year = "2011",

doi = "10.1007/978-3-642-27210-3\_1",

language = "English",

isbn = "9783642272097",

volume = "264",

series = "Communications in Computer and Information Science",

publisher = "Springer-Verlag",

pages = "1--9",

editor = "Kim, \{Tai-hoon \} and Adeli, \{Hojjat \} and Jianhua Ma and Wai-chi Fang and Byeong-Ho Kang and Park, \{Byungjoo \} and Sandnes, \{Frode Eika \} and Lee, \{Kun Chang\}",

booktitle = "U-and E-Service, Science and Technology",

address = "Germany",

note = "UNESST: International Conference on U- and E-Service, Science and Technology, UNESST ; Conference date: 08-12-2011 Through 10-12-2011",

}

Khattak, AM, Pervez, Z, Khan, WA, Lee, SY & Lee, YK 2011, A self evolutionary rule-base. in T Kim, H Adeli, J Ma, W Fang, B-H Kang, B Park, FE Sandnes & KC Lee (eds), U-and E-Service, Science and Technology. vol. 264, Communications in Computer and Information Science, Springer-Verlag, pp. 1-9, UNESST: International Conference on U- and E-Service, Science and Technology, Jeju Island, 8/12/11. https://doi.org/10.1007/978-3-642-27210-3_1

A self evolutionary rule-base. / Khattak, A.M.; Pervez, Z.; Khan, W.A. et al.
U-and E-Service, Science and Technology. ed. / Tai-hoon Kim; Hojjat Adeli; Jianhua Ma; Wai-chi Fang; Byeong-Ho Kang; Byungjoo Park; Frode Eika Sandnes; Kun Chang Lee. Vol. 264 Springer-Verlag, 2011. p. 1-9 (Communications in Computer and Information Science).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A self evolutionary rule-base

AU - Khattak, A.M.

AU - Pervez, Z.

AU - Khan, W.A.

AU - Lee, S.Y

AU - Lee, Y.K.

PY - 2011

Y1 - 2011

N2 - The rapid growth in domain knowledge is the main reason for the evolution of knowledgebase’s maintaining the domain knowledge. Rule-based Decision Support Systems (DSS) are the most effected systems with the growing knowledge. The experts need to continuously update the rule-base for the new knowledge. This manual and periodic updates in rule-base are time consuming and less useful. In this paper we propose a Self Evolutionary Rule-base algorithm for rule-bases of DSS to decrease the burden from experts and also provide updated knowledge on time. To achieve this objective, we develop a generic structure for rules storage that not only provide efficient manipulation of rules but a generic structure for storage of rules regardless of rules nature/format. The detail working of proposed Rule-base system for rules storage and manipulation is provided in this paper. For the proof of concept, we have implemented the Self Evolutionary Rule-base algorithm in Socially Interactive Clinical Decision Support System (SI-CDSS). The focus is on diabetes disease patients and the overall SI-CDSS is deployed in Microsoft Azure environment. In its implementation, Rough Set generated rules are used and the algorithm is executed on Rough Set generated rules.

AB - The rapid growth in domain knowledge is the main reason for the evolution of knowledgebase’s maintaining the domain knowledge. Rule-based Decision Support Systems (DSS) are the most effected systems with the growing knowledge. The experts need to continuously update the rule-base for the new knowledge. This manual and periodic updates in rule-base are time consuming and less useful. In this paper we propose a Self Evolutionary Rule-base algorithm for rule-bases of DSS to decrease the burden from experts and also provide updated knowledge on time. To achieve this objective, we develop a generic structure for rules storage that not only provide efficient manipulation of rules but a generic structure for storage of rules regardless of rules nature/format. The detail working of proposed Rule-base system for rules storage and manipulation is provided in this paper. For the proof of concept, we have implemented the Self Evolutionary Rule-base algorithm in Socially Interactive Clinical Decision Support System (SI-CDSS). The focus is on diabetes disease patients and the overall SI-CDSS is deployed in Microsoft Azure environment. In its implementation, Rough Set generated rules are used and the algorithm is executed on Rough Set generated rules.

KW - Rules

KW - Rule-Base

KW - Decision Support System

KW - Algorithms

KW - Performance

KW - Verification

U2 - 10.1007/978-3-642-27210-3_1

DO - 10.1007/978-3-642-27210-3_1

M3 - Conference contribution

SN - 9783642272097

VL - 264

T3 - Communications in Computer and Information Science

SP - 1

EP - 9

BT - U-and E-Service, Science and Technology

A2 - Kim, Tai-hoon

A2 - Adeli, Hojjat

A2 - Ma, Jianhua

A2 - Fang, Wai-chi

A2 - Kang, Byeong-Ho

A2 - Park, Byungjoo

A2 - Sandnes, Frode Eika

A2 - Lee, Kun Chang

PB - Springer-Verlag

T2 - UNESST: International Conference on U- and E-Service, Science and Technology

Y2 - 8 December 2011 through 10 December 2011

ER -

A self evolutionary rule-base

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Fingerprint

Cite this