Development of a Corruption Detection Algorithm using K-means Clustering
Md. Tawheedul Islam, Mohammad Abu Yousuf · 2018
Corruption in Bangladesh has been a continuing problem. It is arduous to detect all types of corruption but the corruption which effects directly upon the general people from the government or other organizations can be detectable. It has proposed an algorithm combining data mining technique to find corruption. In this paper, an intelligent system has been developed by forming a user evaluation interface. When a person receives a service from an organization then he/she can submit his/her opinion against the specific individual or organization anonymously. After putting their viewpoints, the algorithm having a modified K-means clustering will be executed and output will be sorted for the person of the organization according to their corruption level.