Smart Grievance Redressal System

Addressing the grievances of citizens is a tough task for an administration. Classifying and prioritizing the grievances will make the grievance redressal system more efficient. This paper proposes a software application to identify common issues by analysing multiple grievances, so as to provide the administration, with a view of the important issues that require immediate attention. The software application is developed using state of the art NLP technologies to implement text classification, keyword extraction and keyword clustering on the set of grievances.