Abstract
This chapter provides an overview of prior arts and related studies on mining typed entities and relationships from text. Methods are categorized and organized based on the amounts of human labeled data required in the model training process, which also demonstrates the trajectory of research on reducing human supervision in entity and relation structure mining. We also review techniques developed for learning with noisy labeled data as well as open-domain information extraction, followed by a summary of our contributions.
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© 2018 Springer Nature Switzerland AG
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Ren, X., Han, J. (2018). Literature Review. In: Mining Structures of Factual Knowledge from Text. Synthesis Lectures on Data Mining and Knowledge Discovery. Springer, Cham. https://doi.org/10.1007/978-3-031-01912-8_3
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DOI: https://doi.org/10.1007/978-3-031-01912-8_3
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-00784-2
Online ISBN: 978-3-031-01912-8
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