Online Match-Making Recommendation using Case Based Reasoning and K-Nearest- Neighbors

Abstract

In this project a new approach that uses case-based reasoning (CBR) in match-making for online recommendations is developed. The proposed CBR model uses K-nearest neighbor (KNN) classification for effective and efficient case retrieval. The proposed recommendation system is used to match students with potential employees, based on students’ qualifications and interests, and available projects. The project report outlines the algorithm design, and corresponding architectural model and implementation.