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Construction of the Literature Graph in Semantic Scholar

, , , , , , , , , , , , , , , , , , , , , , and . Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 3 (Industry Papers), page 84--91. New Orleans - Louisiana, Association for Computational Linguistics, (June 2018)
DOI: 10.18653/v1/N18-3011

Abstract

We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery. The resulting literature graph consists of more than 280M nodes, representing papers, authors, entities and various interactions between them (e.g., authorships, citations, entity mentions). We reduce literature graph construction into familiar NLP tasks (e.g., entity extraction and linking), point out research challenges due to differences from standard formulations of these tasks, and report empirical results for each task. The methods described in this paper are used to enable semantic features in www.semanticscholar.org.

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Construction of the Literature Graph in Semantic Scholar - ACL Anthology

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