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Towards building a scholarly big data platform: Challenges, lessons and opportunities.

, , , , , , , , , , and . JCDL, page 117-126. IEEE Computer Society, (2014)

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Implications of Annotation Artifacts in Edge Probing Test Datasets., and . CoNLL, page 575-586. Association for Computational Linguistics, (2023)Curve Separation for Line Graphs in Scholarly Documents., , and . JCDL, page 277-278. ACM, (2016)Scalable algorithms for scholarly figure mining and semantics., , and . SBD@SIGMOD, page 1. ACM, (2016)Scholarly big data information extraction and integration in the CiteSeerχ digital library., , , , and . ICDE Workshops, page 68-73. IEEE Computer Society, (2014)Automatic Extraction of Figures from Scholarly Documents., , and . DocEng, page 47-50. ACM, (2015)Intent Features for Rich Natural Language Understanding., , , and . NAACL-HLT (Industry Papers), page 214-221. Association for Computational Linguistics, (2021)Digital Library and Archiving for Qatar., , , , and . Bull. IEEE Tech. Comm. Digit. Libr., (2015)Automatic Summary Generation for Scientific Data Charts., , and . AAAI Workshop: Scholarly Big Data, volume WS-16-13 of AAAI Technical Report, AAAI Press, (2016)978-1-57735-759-9.HESDK: A Hybrid Approach to Extracting Scientific Domain Knowledge Entities., , , , and . JCDL, page 241-244. IEEE Computer Society, (2017)Machine Reading, Fast and Slow: When Do Models Ünderstand" Language?, , and . COLING, page 78-93. International Committee on Computational Linguistics, (2022)