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Collaborative Writing Tools for Predicting Verb Tense Using Syntax Parsing on Learning Networks

Collaborative Writing Tools for Predicting Verb Tense Using Syntax Parsing on Learning Networks

Enas Ali Mohammed, Zinah Abdulridha Abutiheen, Hafedh Hameed Hussein
Copyright: © 2022 |Volume: 18 |Issue: 2 |Pages: 10
ISSN: 1548-3673|EISSN: 1548-3681|EISBN13: 9781799893875|DOI: 10.4018/IJeC.304042
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MLA

Mohammed, Enas Ali, et al. "Collaborative Writing Tools for Predicting Verb Tense Using Syntax Parsing on Learning Networks." IJEC vol.18, no.2 2022: pp.1-10. http://doi.org/10.4018/IJeC.304042

APA

Mohammed, E. A., Abutiheen, Z. A., & Hussein, H. H. (2022). Collaborative Writing Tools for Predicting Verb Tense Using Syntax Parsing on Learning Networks. International Journal of e-Collaboration (IJeC), 18(2), 1-10. http://doi.org/10.4018/IJeC.304042

Chicago

Mohammed, Enas Ali, Zinah Abdulridha Abutiheen, and Hafedh Hameed Hussein. "Collaborative Writing Tools for Predicting Verb Tense Using Syntax Parsing on Learning Networks," International Journal of e-Collaboration (IJeC) 18, no.2: 1-10. http://doi.org/10.4018/IJeC.304042

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Abstract

Collaborative writing tools and Natural language processing are plays a vital role in learning networks. These tools are involved with the dealings among computer systems and human languages. It processes the data through syntax analysis, parsing and lexical analysis, and etc. Syntax analysis is used for syntactic parsing deals with the syntactic structure of a sentence. The collaborative writing tools and natural language processing applications are used for verb tense prediction and it it encodes the temporal order of activities in a sentence. Recognizing the syntactic structure is beneficial in identifying the means of a sentence. The model in this paper is introduced to predict verb tense based on lexical and syntactic features. This model works on English articles, every article will be split to sentences using the tokenization process. Every token in sentences will be analyzed and model will parse the sentences the use of tenses algorithms that represent grammar rules of the English language. This model is given precise accuracy when it is examined on articles/ stories.

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