Multithreading Approach to Process Real-Time Updates in KNN Algorithms

K-Nearest Neighbors algorithm (KNN) is the core of a considerable amount of online services and applications, like recommendation engines, content-classifiers, information retrieval systems, etc. The users of these services change their preferences over time, aggravating the computational challenges of KNN. In this work, we present UpKNN: an efficient thread-based out-of-core approach to take the updates of users preferences into account while it computes the KNN efficiently.