Document Type
Preprint
Publication Date
12-10-2020
Journal / Book Title
Proceedings 2020 IEEE International Conference on Big Data Big Data 2020
Abstract
We propose a novel scalable Web portal called LSOMP (Large Scale Ordinance Mining Portal) to analyze ordinances and their tweets (of the order of thousands and millions). It entails commonsense knowledge (CSK) and natural language processing (NLP), disseminating ordinance-tweet mining results via interactive graphics and Question Answering (QA).
DOI
10.1109/BigData50022.2020.9378354
Montclair State University Digital Commons Citation
Du, Xu; Kowalski, Matthew; Varde, Aparna S.; and Dong, Boxiang, "LSOMP: Large Scale Ordinance Mining Portal" (2020). Department of Computer Science Faculty Scholarship and Creative Works. 662.
https://digitalcommons.montclair.edu/compusci-facpubs/662