@inproceedings{5169d1b04aeb437eb50bbea5c09e8a68,
title = "LSOMP: Large Scale Ordinance Mining Portal",
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).",
author = "Xu Du and Matthew Kowalski and Varde, {Aparna S.} and Boxiang Dong",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 8th IEEE International Conference on Big Data, Big Data 2020 ; Conference date: 10-12-2020 Through 13-12-2020",
year = "2020",
month = dec,
day = "10",
doi = "10.1109/BigData50022.2020.9378354",
language = "English",
series = "Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5662--5664",
editor = "Xintao Wu and Chris Jermaine and Li Xiong and Hu, {Xiaohua Tony} and Olivera Kotevska and Siyuan Lu and Weijia Xu and Srinivas Aluru and Chengxiang Zhai and Eyhab Al-Masri and Zhiyuan Chen and Jeff Saltz",
booktitle = "Proceedings - 2020 IEEE International Conference on Big Data, Big Data 2020",
}