News Article Classification with Clustering using Semi-Supervised Learning

This paper proposes a method for automated classification of news articles from various online news sources into certain labels based on their domain. The work uses concepts of Natural Language Processing and Machine Learning. Concepts in Clustering, including Spherical K-Means Clustering and Incremental Clustering have been explored. The accuracy of the results obtained from the suggested models was encouraging. These results can be used to compare how the interests of different audiences vary for different news sources.