A Novel Method of Parallel GPU Implementation of KNN Used in Text Classification

Abstract

Automatic text classification is useful when websites have huge volume of web pages or other articles. K-Nearest Neighbour (KNN) is a way to classify the domains of text documents. The performance of text classification depends on lots of factors but KNN process contributes most of computational loads. We present a novel method of parallel GPU implementation of KNN with speed-ups of 40 times compared with CPU implementation.