This paper explores how broadcast media organisations can utilize systems that automatically label news articles.
Broadcast media organisations produce many news scripts every day for dissemination as content. Such text data is often reused in the process of producing TV programmes and web news. To efficiently utilise this much data, it is necessary to accurately attach metadata such as labels that indicate the content of the text. However, manually assigning labels takes an enormous amount of time and effort. With the aim of reducing costs, we have developed a system that automatically labels news articles. A major challenge in the multi-label text classification task in the news domain is known as ‘imbalanced learning.’ We proposed a novel...
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