Knowledge Entity Extraction and Text Mining in the Era of Big Data-Reference-Cited by-同舟云学术

Knowledge Entity Extraction and Text Mining in the Era of Big Data

Published:2021-07-02 Issue:3 Volume:5 Page:309-311
ISSN:2543-9251
Container-title:Data and Information Management
language:en
Short-container-title:

Author:

Zhang Chengzhi¹,Mayr Philipp²,Lu Wei³,Zhang Yi⁴

Affiliation:

1. Department of Information Management , Nanjing University of Science and Technology , Nanjing , China

2. GESIS – Leibniz-Institute for the Social Sciences , Köln , Germany

3. School of Information Management , Wuhan University , Wuhan , China

4. Australian Artificial Intelligence Institute , University of Technology Sydney , Sydney , Australia

Publisher

Walter de Gruyter GmbH

Subject

Geology,Ocean Engineering,Water Science and Technology

Link

https://www.sciendo.com/pdf/10.2478/dim-2021-0009

Reference19 articles.

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2. Cabanac, G., Chandrasekaran, M., Frommholz, I., Jaidka, K., Kan, M., Mayr, P., & Wolfram, D. (2016). Report on the joint workshop on bibliometric-enhanced information retrieval and natural language processing for digital libraries (BIRNDL 2016). ACM SIGIR Forum, 50(2), 36–43.

3. Chandrasekaran, M., de Waard, A., Feigenblat, G., Freitag, D., Ghosal, T., Hovy, E., & Shmueli-Scheuer, M. (2020). Proceedings of the first workshop on scholarly document processing. Retrieved from https://www.aclweb.org/anthology/volumes/2020.sdp-1/

4. Chang, X., & Zheng, Q. (2007). Knowledge element extraction for knowledge-based learning resources organization. In H. Leung, F. Li, R. Lau, & Q. Li (Eds.). Advances in Web Based Learning – ICWL 2007. ICWL 2007. Lecture Notes in Computer Science, vol. 4823 (pp. 102–113). Berlin, Heidelberg: Springer. doi: 10.1007/978-3-540-78139-4_10

5. Hou, L., Zhang, J., Wu, O., Yu, T., Wang, Z., Li, Z., & Yao, R. (2020). Method and dataset entity mining in scientific literature: A CNN+ Bi-LSTM model with self-attention. ArXiv Preprint. arXiv:2010.13583

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