Abstract
<i>This article describes the collaboration between BBC News and BBC Research & Development, who are exploring ways to use the BBC’s linear program output and associated production metadata, along with artificial intelligence and machine learning techniques, to segment the programs into individual stories. These segments can then be used to provide chapterized versions of the linear output, make individual stories findable by search and available as items on web pages. Ultimately, by using object-based media (OBM) techniques, these stories can be recombined to provide personalized and/or interactive experiences. We hypothesize that access to individual stories and items instead of entire, undifferentiated programs will be of greater value to audiences and we provide the user testing results that support this. In this article, we explain the approach being taken to recover program metadata and how that can help achieve content segmentation at scale. The article then describes how OBM techniques are being used to automatically combine segmented content to make new interactive and personalized experiences, including the prototype code base and the workflows developed so far. The article concludes with a summary of the key findings from the work to date, including audience benefits, data consistency, and the role of editorial oversight</i>.
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