Abstract
KMKE provides a knowledge engineering approach to integrating knowledge management activities (such as knowledge modeling, knowledge verification, knowledge storage and knowledge querying) into a systematic framework. In this paper, we develop the KMKE knowledge management system based on design patterns and parallel processing. First, several design patterns are applied to develop the KMKE system for enhancing its flexibility and extensibility. Making the KMKE system flexible and extensible is useful to deal with continuous changes originated in knowledge. Second, JAVA programs and CLIPS programs are bound to offer the capability of knowledge inference for the KMKE system. Knowledge verification and knowledge querying can then be performed through the execution of CLIPS rules. Finally, we propose the Parallel CLIPS to shorten the execution time of the KMKE system. Since a large amount of knowledge may increase the execution time substantially, parallelizing the execution of CLIPS rules in cluster system could effectively reduce the search space of the CLIPS inference engine.
| Original language | English |
|---|---|
| Title of host publication | Emerging Intelligent Computing Technology and Applications - 5th International Conference on Intelligent Computing, ICIC 2009, Proceedings |
| Pages | 928-938 |
| Number of pages | 11 |
| DOIs | |
| Publication status | Published - 2009 Nov 11 |
| Event | 5th International Conference on Intelligent Computing, ICIC 2009 - Ulsan, Korea, Republic of Duration: 2009 Sep 16 → 2009 Sep 19 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 5754 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 5th International Conference on Intelligent Computing, ICIC 2009 |
|---|---|
| Country | Korea, Republic of |
| City | Ulsan |
| Period | 09-09-16 → 09-09-19 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Developing the KMKE knowledge management system based on design patterns and parallel processing. / Lai, Lien Fu; Wu, Chao Chin; Huang, Liang Tsung; Chang, Ya Chin.
Emerging Intelligent Computing Technology and Applications - 5th International Conference on Intelligent Computing, ICIC 2009, Proceedings. 2009. p. 928-938 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5754 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Developing the KMKE knowledge management system based on design patterns and parallel processing
AU - Lai, Lien Fu
AU - Wu, Chao Chin
AU - Huang, Liang Tsung
AU - Chang, Ya Chin
PY - 2009/11/11
Y1 - 2009/11/11
N2 - KMKE provides a knowledge engineering approach to integrating knowledge management activities (such as knowledge modeling, knowledge verification, knowledge storage and knowledge querying) into a systematic framework. In this paper, we develop the KMKE knowledge management system based on design patterns and parallel processing. First, several design patterns are applied to develop the KMKE system for enhancing its flexibility and extensibility. Making the KMKE system flexible and extensible is useful to deal with continuous changes originated in knowledge. Second, JAVA programs and CLIPS programs are bound to offer the capability of knowledge inference for the KMKE system. Knowledge verification and knowledge querying can then be performed through the execution of CLIPS rules. Finally, we propose the Parallel CLIPS to shorten the execution time of the KMKE system. Since a large amount of knowledge may increase the execution time substantially, parallelizing the execution of CLIPS rules in cluster system could effectively reduce the search space of the CLIPS inference engine.
AB - KMKE provides a knowledge engineering approach to integrating knowledge management activities (such as knowledge modeling, knowledge verification, knowledge storage and knowledge querying) into a systematic framework. In this paper, we develop the KMKE knowledge management system based on design patterns and parallel processing. First, several design patterns are applied to develop the KMKE system for enhancing its flexibility and extensibility. Making the KMKE system flexible and extensible is useful to deal with continuous changes originated in knowledge. Second, JAVA programs and CLIPS programs are bound to offer the capability of knowledge inference for the KMKE system. Knowledge verification and knowledge querying can then be performed through the execution of CLIPS rules. Finally, we propose the Parallel CLIPS to shorten the execution time of the KMKE system. Since a large amount of knowledge may increase the execution time substantially, parallelizing the execution of CLIPS rules in cluster system could effectively reduce the search space of the CLIPS inference engine.
UR - http://www.scopus.com/inward/record.url?scp=70350770699&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70350770699&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-04070-2_98
DO - 10.1007/978-3-642-04070-2_98
M3 - Conference contribution
AN - SCOPUS:70350770699
SN - 3642040691
SN - 9783642040696
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 928
EP - 938
BT - Emerging Intelligent Computing Technology and Applications - 5th International Conference on Intelligent Computing, ICIC 2009, Proceedings
ER -