LSOMP: Large Scale Ordinance Mining Portal

Xu Du, Matthew Kowalski, Aparna Varde, Boxiang Dong

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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).

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Big Data, Big Data 2020
EditorsXintao Wu, Chris Jermaine, Li Xiong, Xiaohua Tony Hu, Olivera Kotevska, Siyuan Lu, Weijia Xu, Srinivas Aluru, Chengxiang Zhai, Eyhab Al-Masri, Zhiyuan Chen, Jeff Saltz
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5662-5664
Number of pages3
ISBN (Electronic)9781728162515
DOIs
StatePublished - 10 Dec 2020
Event8th IEEE International Conference on Big Data, Big Data 2020 - Virtual, Atlanta, United States
Duration: 10 Dec 202013 Dec 2020

Publication series

NameProceedings - 2020 IEEE International Conference on Big Data, Big Data 2020

Conference

Conference8th IEEE International Conference on Big Data, Big Data 2020
CountryUnited States
CityVirtual, Atlanta
Period10/12/2013/12/20

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