IBC2024 Tech Papers: Multi-Label Indexing Technology for News with AI-based Text Processing

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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IET announce Best of IBC Technical Papers

The IET have announced the publication of The best of IET and IBC 2024 from IBC2024, once again showcasing the groundbreaking research presented through the papers. The papers have been selected by IBC’s Technical Papers Committee for being novel, topical, analytical and well-written and which have the potential to make a significant impact upon the media industry. 327 papers were submitted this year, and after a rigorous selection process this publication features the ten papers deemed by the judges to be the best.

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