Practical skills of business English correspondence writing based on data mining algorithm

English correspondence writing has become a necessary skill for every scientific researcher and high-tech talents. An English correspondence writing auxiliary writing system can help nonnative English speakers make up for the lack of professional expression. The key factor of business English corres...

Full description

Bibliographic Details
Main Authors: Liu, Danqing, Habil, Hadina
Format: Article
Language:English
Published: Hindawi Limited 2022
Subjects:
Online Access:http://eprints.utm.my/98564/1/DanqingLiu2022_PracticalSkillsofBusinessEnglishCorrespondence.pdf
_version_ 1796866645607579648
author Liu, Danqing
Habil, Hadina
author_facet Liu, Danqing
Habil, Hadina
author_sort Liu, Danqing
collection ePrints
description English correspondence writing has become a necessary skill for every scientific researcher and high-tech talents. An English correspondence writing auxiliary writing system can help nonnative English speakers make up for the lack of professional expression. The key factor of business English correspondence writing system is the construction of knowledge base. To improve the business English correspondence writing knowledge base, we need to mine frequent patterns of sentences in each category. The purpose of this topic is to improve and supplement the knowledge base for the business English correspondence writing system and propose frequent pattern mining for sentences in each category, so as to improve the writing knowledge base for the business English correspondence writing system. Firstly, we crawl a large number of business English letters and telegrams from the Internet, extract the relevant summary information, then store it, and preliminarily construct a corpus based on sentences. Then, we do some research on the structure of business English correspondence abstracts, mark the sentences in the corpus and count the relevant information, and have a certain understanding of their writing methods. Finally, we mine frequent patterns for sentences in each category, so as to improve the knowledge base of summary writing for the business English correspondence writing system. In the experiment, we use the classical FP growth algorithm as the mining method. The experiment shows that the frequent patterns between 3 and 6 words have been mined to a certain extent. By gradually improving the mining strategy, the quality of mining results has been improved and the writing effect of business English correspondence of scientific researchers has been improved.
first_indexed 2024-03-05T21:15:16Z
format Article
id utm.eprints-98564
institution Universiti Teknologi Malaysia - ePrints
language English
last_indexed 2024-03-05T21:15:16Z
publishDate 2022
publisher Hindawi Limited
record_format dspace
spelling utm.eprints-985642023-01-17T09:23:03Z http://eprints.utm.my/98564/ Practical skills of business English correspondence writing based on data mining algorithm Liu, Danqing Habil, Hadina PE English English correspondence writing has become a necessary skill for every scientific researcher and high-tech talents. An English correspondence writing auxiliary writing system can help nonnative English speakers make up for the lack of professional expression. The key factor of business English correspondence writing system is the construction of knowledge base. To improve the business English correspondence writing knowledge base, we need to mine frequent patterns of sentences in each category. The purpose of this topic is to improve and supplement the knowledge base for the business English correspondence writing system and propose frequent pattern mining for sentences in each category, so as to improve the writing knowledge base for the business English correspondence writing system. Firstly, we crawl a large number of business English letters and telegrams from the Internet, extract the relevant summary information, then store it, and preliminarily construct a corpus based on sentences. Then, we do some research on the structure of business English correspondence abstracts, mark the sentences in the corpus and count the relevant information, and have a certain understanding of their writing methods. Finally, we mine frequent patterns for sentences in each category, so as to improve the knowledge base of summary writing for the business English correspondence writing system. In the experiment, we use the classical FP growth algorithm as the mining method. The experiment shows that the frequent patterns between 3 and 6 words have been mined to a certain extent. By gradually improving the mining strategy, the quality of mining results has been improved and the writing effect of business English correspondence of scientific researchers has been improved. Hindawi Limited 2022-07 Article PeerReviewed application/pdf en http://eprints.utm.my/98564/1/DanqingLiu2022_PracticalSkillsofBusinessEnglishCorrespondence.pdf Liu, Danqing and Habil, Hadina (2022) Practical skills of business English correspondence writing based on data mining algorithm. Scientific Programming, 2022 (NA). pp. 1-10. ISSN 1058-9244 http://dx.doi.org/10.1155/2022/2465095 DOI:10.1155/2022/2465095
spellingShingle PE English
Liu, Danqing
Habil, Hadina
Practical skills of business English correspondence writing based on data mining algorithm
title Practical skills of business English correspondence writing based on data mining algorithm
title_full Practical skills of business English correspondence writing based on data mining algorithm
title_fullStr Practical skills of business English correspondence writing based on data mining algorithm
title_full_unstemmed Practical skills of business English correspondence writing based on data mining algorithm
title_short Practical skills of business English correspondence writing based on data mining algorithm
title_sort practical skills of business english correspondence writing based on data mining algorithm
topic PE English
url http://eprints.utm.my/98564/1/DanqingLiu2022_PracticalSkillsofBusinessEnglishCorrespondence.pdf
work_keys_str_mv AT liudanqing practicalskillsofbusinessenglishcorrespondencewritingbasedondataminingalgorithm
AT habilhadina practicalskillsofbusinessenglishcorrespondencewritingbasedondataminingalgorithm