Publishers are aware of the challenges in transitioning to digital-led publishing processes and a data-driven business landscape. On the one hand, many do not know how to unlock the value of their content and data. On the other, publishers are leveraging data science and Artificial Intelligence (AI) to unlock the value. These publishers understand the importance of a sound content classification system, how AI-led tagging could transform their industry, and knowledge graphs could revolutionize the tagging paradigm.
However, the total cost of ownership and product differentiation is more critical for the financially stretched publishing sector than ever. Therefore, publishers should first implement a knowledge graph to reduce the total cost of ownership and improve the efficiency of innovation. This would help them to manage subject metadata and make it available across their enterprise. Second, they should use a scalable AI auto-tagging service and then apply metadata to new content sent to it for prediction. Integrating this with a content management system and publishing stack allows an automated tagging system to learn continuously and react quickly to new concepts in the ever-changing publishing world.
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