Legal Expert System for Critical Decision-Making Using Machine Learning with Natural Language Processing Technique (A Case Study of INEC Nigeria)

Source abstract

This research aims to develop a legal expert system for critical decision-making using machine learning with natural language processing technique, focusing on the case study of the Independent National Electoral Commission (INEC) in Nigeria. The expert system is designed to assist legal practitioners and decision-makers in the electoral process by providing accurate and timely information on legal matters related to elections. The research involves the collection and analysis of legal documents, case laws, and election regulations (Electoral Act 2022) to build a comprehensive knowledge base for the expert system. Machine learning algorithms was employed to train the system to understand and interpret legal language, while natural language processing techniques enable the system to process and analyse large volumes of text data efficiently. The expert system is designed to provide recommendations and insights on legal issues such as voter registration, candidate eligibility, electoral dispute resolution, and compliance with electoral laws. It is also capable of handling complex legal scenarios and providing explanations for its decision making, it’s a valuable tool for legal practitioners and decision-makers in the electoral process. The successful implementation of this research contributes to improving the efficiency and accuracy of legal decision-making in electoral matters, ultimately enhancing the transparency and fairness of the electoral process in Nigeria.