Newsaday: A personalized thai news recommendation system

Abstract

Nowadays, news are available ubiquitously in heterogeneous forms, from both offline and online sources. An example of offline news resource includes newspaper which contains only text and pictures. Online news articles have recently emerged to enhance news consuming experiences, such as embedding videos to allow readers to illustrate real situations. However, to read news articles online, users may have faced problems. For example, they are bombarded with articles which are not related to their interest. From this problem, it would be better if users can manage their preferences to perceive news. Therefore, Newsaday is proposed and prototyped to mitigate such issues. Newsaday is a personalized Thai news recommendation application to support users to gather information from online news websites. The system applies natural language processing algorithms to pull news articles from online news websites. If users want the system to recommend news articles, they can specify their preferences either from explicitly choosing the news categories or implicitly indicating favorite news articles they have read. Then, the system adaptively learns the uses' preferences, and uses the information to retrieve relevant news articles.