It’s a part of the knowledge base expert system that consists of a set of cases and heuristics, which are accumulated from both primary and secondary resources to generate expert solutions for migrant cases.
Published in Chapter:
A Knowledge-Based Recommender Framework to Recommend Destination Country for Human Migrants (KBRF): The Case of Ethiopia in Africa
Nilamadhab Mishra (VIT Bhopal University, India), Baye Yemataw (Debre Berhan University, Ethiopia), and Kishore Kumar P. K. (University of Technology and Applied Sciences, Oman)
Copyright: © 2022
|Pages: 30
DOI: 10.4018/978-1-7998-2395-7.ch005
Abstract
Human migration is a challenging process in Ethiopia, where special illegal human migrants cross different border countries without any basic information or knowledge. Due to this, there is the difficulty of getting a vast amount of information to know the destination countries. They go without any information, which also wastes more time, cost, violates their human rights, and endangers their lives. This study used a KBRF to assess the user input and compare them with the stored cases. For this, 75,920 cases were collected from MoLSA and central statistical agencies with and attributes selected for the query of users as well as for their solution. The best solutions are displayed for a user after the similarity calculation of the query and the stored cases. Then the users can decide on which similar cases satisfy their needs. KBRF has an average performance, recall, and precision score of 92% (4.60), 0.91 (91%), and 0.63 (63%), respectively, from domain experts and system performance.