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Overview
In this chapter, we discuss approaches leveraging distant supervision for relation extraction. We start by introducing the key ideas behind distant supervision as well as their main shortcomings. We then discuss approaches that improve over the basic method, including approaches based on the at-least-one-principle along with their extensions for handling false negative labels, and approaches leveraging topic models. We also describe embeddings-based methods including methods leveraging convolutional neural networks. Finally, we discuss how to take advantage of auxiliary information to improve relation extraction.
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Definition 1
A knowledge graph, or knowledge base, is a semantic network defined as a set of triples (s, p, o) specifying that a node s (subject) is connected to another node o (object) by the property p. Sets of such triples form a directed graph, where nodes in the graph represent the subject and object in...
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Smirnova, A., Audiffren, J., Cudré-Mauroux, P. (2019). Distant Supervision from Knowledge Graphs. In: Sakr, S., Zomaya, A.Y. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-77525-8_285
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DOI: https://doi.org/10.1007/978-3-319-77525-8_285
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