Cross-Organizational Information Systems: A Case for Educational Data Mining

Establishing a new organization is becoming more difficult day by day due to the extremely competitive business environment. A new organization may not have enough experience to survive in the competitive market; which in turn may push down the reputation of the organization and the trust of the investors. The goal of this research project work is to design a framework for the cross-organizational information system for assessment and decision making using machine learning with the emphasis on the educational sector. In the proposed framework, organizations share information (even raw data) with each other and machine learning tool will be utilized for shared data analysis for decision making for a particular organization. A framework like this can help new organizations to get benefit from the experience of other ‘older’ organizations and institutions. Such knowledge-based machine learning system helps to improve the organizational capability of newly established institutions. As an implementation of the framework, we build a fuzzy system that can effectively work as a cross-platform system for educational entities.

@article{Ansari2017,
  title     = {Cross-Organizational Information Systems: A Case for Educational Data Mining},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {11},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Gufran Ahmad Ansari and Mohammad Tanvir Parvez and Ali Al Khalifah},
  doi       = {10.14569/IJACSA.2017.081122},
  url       = {https://doi.org/10.14569/IJACSA.2017.081122}
}