Effective Management Framework for Fuzzy Databases

Mohammadi, M.R.

doi:10.22034/apj.2022.699800

Effective Management Framework for Fuzzy Databases

Document Type : Original Research Article

Author

M.R. Mohammadi

Department of Computer Science, University of Tehran, Tehran, Iran

10.22034/apj.2022.699800

Abstract

Nowadays, with the increasing use of information systems and the movement of organizations towards knowledge-based information systems, the effective management of data and information is one of the important concerns and fundamental operational areas of information and communication technology. In different fields of application, database management can be done with different techniques and approaches. Fuzzy logic as an effective technique is able to create an effective infrastructure and approach for the systematic management of distributed database systems. One of these fields is related to the application of fuzzy systems theory in databases, information retrieval, expert systems and knowledge base. The most important issue that arises in fuzzy databases is how to deal with the phenomenon of uncertainty. In fuzzy logic applications, non-numeric values are often used to facilitate the expression of rules and facts of databases. In this article, the effective management framework of the fuzzy database is examined.

Keywords

Database

Fuzzy Logic

Management System

Framework

Distributed Data

[1] Fernandez-Basso, C., Ruiz, M. D., & Martin-Bautista, M. J. (2020). A fuzzy mining approach for energy efficiency in a Big Data framework. IEEE Transactions on Fuzzy Systems, 28(11), 2747-2758.

[2] Keskin, S., & Yazıcı, A. (2022). Modeling and Querying Fuzzy SOLAP-Based Framework. ISPRS International Journal of Geo-Information, 11(3), 191.

[3] Phang, K. K. (1997). Development of fuzzy database systems. Malaysian Journal of computer science, 10(1), 42-46.

[4] Mahmood, N., Burney, S. A., & Ahsan, K. (2012). Generic Temporal and Fuzzy Ontological Framework (GTFOF) for Developing Temporal-Fuzzy Database Model for Managing Patient's Data. J. Univers. Comput. Sci., 18(2), 177-193.

[5] Keskin, S., & Yazıcı, A. (2022). FSOLAP: A fuzzy logic-based spatial OLAP framework for effective predictive analytics. Expert Systems with Applications, 118961.

[6] Barranco, C. D., Campaña, J. R., & Medina, J. M. (2008). Towards a fuzzy object-relational database model. In Handbook of Research on Fuzzy Information Processing in Databases (pp. 435-461). IGI Global.

[7] Fan, T., Yan, L., & Ma, Z. (2020). Storing and querying fuzzy RDF (S) in HBase databases. International Journal of Intelligent Systems, 35(4), 751-780.

[8] Bordogna, G., & Pasi, G. (Eds.). (2000). Recent issues on fuzzy databases (Vol. 53). Springer Science & Business Media.

[9] Abdul, M., Muhammad, A. M., Mustapha, N., Muhammad, S., & Ahmad, N. (2014). Database workload management through CBR and fuzzy based characterization. Applied Soft Computing, 22, 605-621.

[10] Kraft, D. H., & Petry, F. E. (1997). Fuzzy information systems: managing uncertainty in databases and information retrieval systems. Fuzzy sets and systems, 90(2), 183-191.

[11] Ling, T. C., Yaacob, M. H., & Phang, K. K. (1997, December). Fuzzy database framework-relational versus object-oriented model. In Proceedings Intelligent Information Systems. IIS'97 (pp. 246-250). IEEE.

[12] Centobelli, P., Cerchione, R., & Esposito, E. (2018). Aligning enterprise knowledge and knowledge management systems to improve efficiency and effectiveness performance: A three-dimensional Fuzzy-based decision support system. Expert Systems with Applications, 91, 107-126.

[13] Li, D., & Liu, D. (1990). A fuzzy Prolog database system. John Wiley & Sons, Inc..

[14] Drissi, A., Nait-Bahloul, S., Benouaret, K., & Benslimane, D. (2019). Horizontal fragmentation for fuzzy querying databases. Distributed and Parallel Databases, 37(3), 441-468.

[15] Dwibedy, D., Sahoo, L., & Dutta, S. (2013). A New Approach to Object Based Fuzzy Database Modeling. International Journal of Soft Computing and Engineering (IJSCE), 3(1), 182-186.

[16] Shiono, Y., Goto, T., Yoshizumi, T., & Tsuchida, K. (2021, June). Fuzzy Database and Interface to Analyze Management System Operations. In Proceedings of the The 8th International Virtual Conference on Applied Computing & Information Technology (pp. 19-26).

[17] Thangaraj, M., & Vijayalakshmi, C. R. (2016). An efficient multi relational framework using fuzzy rule-based classification technique. International Journal of Data Mining, Modelling and Management, 8(4), 348-368.

[18] Keskin, S. (2021, September). Management of Complex and Fuzzy Queries Using a Fuzzy SOLAP-Based Framework. In International Conference on Flexible Query Answering Systems (pp. 109-126). Springer, Cham.

[19] Campaña, J. R., Medina, J. M., & Vila, M. A. (2014). Semantic data management using fuzzy relational databases. In Flexible Approaches in Data, Information and Knowledge Management (pp. 115-140). Springer, Cham.