A chatbot, a recommender system and a queueing system
The goal is to create a system that transcribes complaints, and utilizes natural language processing techniques and ranking algorithms to search for applicable jurisprudence. The results will then be transmitted to competent legal service providers such as the PAO, legal clinics and law firms for queueing and evaluation.
A system that transcribes the details of a client's complaint in real-time, then feeds it to a recommender system that will determine whether or not there is an actionable case. The generated results from the ranking algorithm will be forwarded to legal service providers for their evaluation.
Justice delayed is justice denied. One of the reasons poor people are afraid of going to court is the notion that litigation is expensive and the procedure can be bureaucratic. As an alternative, they seek the help of public affairs shows, which is not the right avenue to voice concerns and protect individual rights and privacy. A transcription tool will be able to help legal researchers by gathering the narrative of a client's complaint and generating a digital report. The digital report will be fed to a recommender system which utilizes heuristics and machine learning to automatically assess the likelihood of an actionable case. This would greatly enhance the efficiency of legal research by seeking similar jurisprudence and ranking them in terms of likeness. For unique and unprecedented complaints, they may be forwarded to the legal staff of the policy-making body.