Machine Propositional Model Research Based on Natural Language Processing

Jie Zhou, Yuqi Sun, Baoping Wang, Zheng Wang, Kun Li, Xujia Li

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

Abstract

Machine propositions are the research frontier of natural language processing technology, and the core of the technology path is the result of the development of reading comprehension and question answering systems. Machine propositions can help save a lot of manpower and time, especially in the case of the continuous development of the Covid-19, and help the teaching acceptance and learning evaluation of online learning. At present, the simultaneous pursuit of autonomous propositions and precision requirements in the academic field of machine propositions is the research focus and difficulty.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages599-602
Number of pages4
ISBN (Electronic)9781665416061
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022 - Changchun, China
Duration: 25 Feb 202227 Feb 2022

Publication series

Name2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022

Conference

Conference2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022
Country/TerritoryChina
CityChangchun
Period25/02/2227/02/22

Keywords

  • Machine proposition
  • automatic scoring
  • machine reading comprehension
  • text summarization

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