Scientific document processing: challenges for modern learning methods
Published in International Journal on Digital Libraries, 2023
Neural network models enjoy success on language tasks related to Web documents, including news and Wikipedia articles. However, the characteristics of scientific publications pose specific challenges that have yet to be satisfactorily addressed: the discourse structure of scientific documents crucial in scholarly document processing (SDP) tasks, the interconnected nature of scientific documents, and their multimodal nature. We survey modern neural network learning methods that tackle these challenges: those that can model discourse structure and their interconnectivity and use their multimodal nature. We also highlight efforts to collect large-scale datasets and tools developed to enable effective deep learning deployment for SDP. We conclude with a discussion on upcoming trends and recommend future directions for pursuing neural natural language processing approaches for SDP.
Citation: Abhinav Ramesh Kashyap, Yajing Yang & Min-Yen Kan (2023). Scientific document processing: challenges for modern learning methods. International Journal on Digital Libraries, 24, 283–309.
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Recommended citation: Kashyap, Abhinav Ramesh, Yajing Yang, and Min-Yen Kan. (2023). "Scientific document processing: challenges for modern learning methods." International Journal on Digital Libraries. 24, 283–309.
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