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Current trends in the integration of case-based reasoning and semantic Web

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General Information
Title
Current trends in the integration of case-based reasoning and semantic Web
Type
Article
Main Author
Aslina Saad
Additional Authors
  • Shahnita Shaharin
  • Mashitoh Hashim
  • Nor Hasbiah Ubaidullah
Subject
L Education
Language Code
eng
Bibliographic Details
Place of Production
Tanjong Malim
Publisher
Fakulti Seni, Komputeran dan Industri Kreatif
Year of publication
2019
Degree Type
Others
Corporate Name
Universiti Pendidikan Sultan Idris

Abstract

Case-Based Reasoning (CBR) and semantic web are intelligent methods or techniques that have been used in number of critical fields. Both methods have unique strengths and immense potential in problem solving in a wide range of domains. The main aim of this paper is to highlight an overview of the current efforts by researchers to integrate the capabilities of both techniques of CBR and semantic web. Through an analysis on the current literature involving 21 related articles, a taxonomy was developed indicating there were three stands of research focus. First, 38% (n = 8) of the articles involved studies of new methods that combined both techniques. Second, 33.3% (n = 7) of the articles dealt with the development of working frameworks or new approaches. Third, 28.6% (n = 6) of the articles focused on efforts to develop systems that integrated both techniques. In particular, the analysis showed that the medical field was the dominant field in which the integrated technique was widely used in solving medical-related problems. In light of this emerging potential, both techniques can also be applied to help provide efficient and effective problem-solving solutions for other important fields.  

References

Ahmed, U., Khalid, N., Ammar, A., & Shah, M. H. (2017). Assessing moderation of employee engagement on the relationship between work discretion, job clarity and business performance in the banking sector of Pakistan. Asian Economic and Financial Review, 7(12), 1197-121. https://doi.org/10.18488/journal.aefr.2017.712.1197.1210

Ahmed, U., Majid, A. H. A., & Zin, M. M. (2016). Moderation of meaningful work on the relationshipof supervisor support and coworker support with work engagement. The Journal of Business, Economics, and Environmental Studies (JBEES), 6(3), 15-20.

Aamodt, A., & Plaza, E. (1994). Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI communications, 7(1), 39-59.

Aarnio, P., Seilonen, I., & Friman, M. (2014, September). Semantic repository for case-based reasoning in CBM services. In Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA) (pp. 1-8). IEEE.

Amailef, K., & Lu, J. (2013). Ontology-supported case-based reasoning approach for intelligent mGovernment emergency response services. Decision Support Systems, 55(1), 79-97.

Bergmann, R., Kolodner, J., & Plaza, E. (2005). Representation in case-based reasoning. The Knowledge Engineering Review, 20(03), 209-213.

Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific American, 284(5), 28-37.

Bouhana, A., Zidi, A., Fekih, A., Chabchoub, H., & Abed, M. (2015). An ontology-based CBR approach for personalized itinerary search systems for sustainable urban freight transport. Expert Systems with Applications, 42(7), 3724-3741.

Chang, J. W., Lee, M. C., & Wang, T. I. (2016). Integrating a semantic-based retrieval agent into casebased reasoning systems: A case study of an online bookstore. Computers in Industry, 78, 29-42.

d'Aquin, M., Lieber, J., & Napoli, A. (2013). Decentralized case-based reasoning and Semantic Web technologies applied to decision support in oncology. The Knowledge Engineering Review, 28(04), 425-449.

Douali, N., Csaba, H., De Roo, J., Papageorgiou, E. I., & Jaulent, M. C. (2014). Diagnosis support system based on clinical guidelines: comparison between case-based fuzzy cognitive maps and Bayesian networks. Computer methods and programs in biomedicine, 113(1), 133-143.

Douali, N., De Roo, J., Papageorgiou, E. I., & Jaulent, M. C. (2011, June). Case-Based Fuzzy Cognitive Maps (CBFCM): new method for medical reasoning: comparison study between CBFCM/FCM. In Fuzzy Systems (FUZZ), 2011 IEEE International Conference (pp. 844-850). IEEE.

El-Sappagh, S., Elmogy, M., & Riad, A. M. (2015). A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis. Artificial intelligence in medicine, 65(3), 179-208.

Flores, R. L., Belaud, J. P., Negny, S., & Le Lann, J. M. (2015). Open computer aided innovation to promote innovation in process engineering. Chemical Engineering Research and Design, 103, 90- 107.

Kolodner, J. (2014). Case-based reasoning. Morgan Kaufmann.

Lee, C. H., Wang, Y. H., & Trappey, A. J. (2015). Ontology-based reasoning for the intelligent handling of customer complaints. Computers & Industrial Engineering, 84, 144-155.

Martin, A., Emmenegger, S., & Wilke, G. (2013, November). Integrating an enterprise architecture ontology in a case-based reasoning approach for project knowledge. In Enterprise Systems Conference (ES), 2013 (pp. 1-12). IEEE.

Minhas, S., Juzek, C., & Berger, U. (2012). Ontology based Intelligent assistance system to support manufacturing activities in a distributed manufacturing environment. Procedia CIRP, 3, 215-220.

Pal, K., & Karakostas, B. (2014). A multi agent-based service framework for supply chain management. Procedia Computer Science, 32, 53-60.

Preethi, N., & Devi, T. (2013, January). New Integrated Case And Relation Based (CARE) Page Rank Algorithm. In Computer Communication and Informatics (ICCCI), 2013 International Conference (pp. 1-8). IEEE.

Recio-García, J. A., González-Calero, P. A., & Díaz-Agudo, B. (2014). Template-based design in colibri studio. Information Systems, 40, 168-178.

Saïs, F., & Thomopoulos, R. (2014). Ontology-aware prediction from rules: A reconciliation-based approach. Knowledge-Based Systems, 67, 117-130.

Sanchez, E., Peng, W., Toro, C., Sanin, C., Graña, M., Szczerbicki, E., ... & Brualla, L. (2014). Decisional DNA for modeling and reuse of experiential clinical assessments in breast cancer diagnosis and treatment. Neurocomputing, 146, 308-318.

Syu, Y., Fanjiang, Y. Y., Kuo, J. Y., & Ma, S. P. (2011, July). An automated workflow composition tosemantic web services. In Machine Learning and Cybernetics (ICMLC), 2011 International Conference on (Vol. 2, pp. 903-907). IEEE.

Wang,  H. T., & Tansel, A. U. (2013). MedCase: a template medical case store for case-based reasoning in medical decision support. In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (pp. 962-967). ACM.

Yuan, X., Lee, J. H., Kim, S. J., & Kim, Y. H. (2013). Toward a user-oriented recommendation system for real estate websites. Information Systems, 38(2), 231-243.

Zidi, A., Bouhana, A., Abed, M., & Fekih, A. (2014). An ontology-based personalized retrieval model using case base reasoning. Procedia Computer Science, 35, 213-222.

 


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