Unsupervised topic extraction from twitter: A feature-pivot approach
Funding Sponsor
Race and Difference Initiative, Emory University
Author's Department
Computer Science & Engineering Department
Find in your Library
https://doi.org/10.5220/0007959001850192
Document Type
Research Article
Publication Title
WEBIST 2019 - Proceedings of the 15th International Conference on Web Information Systems and Technologies
Publication Date
1-1-2019
doi
10.5220/0007959001850192
First Page
185
Last Page
192
Recommended Citation
APA Citation
GabAllah, N. A.
&
Rafea, A.
(2019). Unsupervised topic extraction from twitter: A feature-pivot approach. WEBIST 2019 - Proceedings of the 15th International Conference on Web Information Systems and Technologies, 185–192.
10.5220/0007959001850192
https://fount.aucegypt.edu/faculty_journal_articles/1075
MLA Citation
GabAllah, Nada, et al.
"Unsupervised topic extraction from twitter: A feature-pivot approach." WEBIST 2019 - Proceedings of the 15th International Conference on Web Information Systems and Technologies, 2019, pp. 185–192.
https://fount.aucegypt.edu/faculty_journal_articles/1075