Unsupervised Concept Categorization and Extraction from Scientific Document Titles

Author:

Krishnan Adit1,Sankar Aravind1,Zhi Shi1,Han Jiawei1

Affiliation:

1. University of Illinois at Urbana-Champaign, Urbana-Champaign, IL, USA

Funder

NIGMS

U.S. Army Research Lab

National Science Foundation

Publisher

ACM

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exploring the Challenges and Limitations of Unsupervised Machine Learning Approaches in Legal Concepts Discovery;Advances in Soft Computing;2023-11-09

2. Context-based extraction of concepts from unstructured textual documents;Information Sciences;2022-04

3. Constructing an Educational Knowledge Graph with Concepts Linked to Wikipedia;Journal of Computer Science and Technology;2021-09-30

4. A Comparative Study of Sequence Tagging Methods for Domain Knowledge Entity Recognition in Biomedical Papers;Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020;2020-08

5. Bringing Shape to Textual Data – A Feasible Demonstration;Mehran University Research Journal of Engineering and Technology;2019-10-01

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