Tagging can be seen as the action of connecting a relevant user-defined keyword to a document, image or video, which helps user to better organize and share their collections of interesting stuff. With the rapid growth of Web 2.0, tagged data is becoming more and more abundant on the social network websites. An interesting problem is how to automate the process of making tag recommendations to users when a new resource becomes available.
In this case study, a machine learning perspective is used to automate the process of tag recommendation for news articles.
Suggest tags for the news articles based on the text content in the headline, synopsis and article text.