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基于数据分析和关联规则的小样本环境下文学课程兴趣影响因素评价模型

An Evaluation Model for the Influence Factors of Interest in Literature Courses Based on Data Analysis and Association Rules in a Small-Sample Environment.

机构信息

Foreign Languages School, Weifang College, Weifang, Shandong 261061, China.

出版信息

J Environ Public Health. 2022 Sep 9;2022:1900509. doi: 10.1155/2022/1900509. eCollection 2022.

DOI:10.1155/2022/1900509
PMID:36120144
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9481340/
Abstract

The primary tools for developing pupils' creativity, capacity for verbal expression, and spiritual growth are literary reading and writing. Literature is a sort of art that elicits feelings and expresses the author's comprehension and outlook on social life via the use of language. Reading and writing literary works helps students develop their aesthetic sensibilities and capacity to create compelling images, as well as their spirituality and wisdom. This study suggests a data mining-based optimal design approach for analyzing association rules of influencing aspects of interest in literary courses. To increase the frequency and accuracy of data mining, association rules are used to obtain the association mapping relationship between data sets of influencing factors of interest in literature courses. Rough set theory is then used to distinguish between the feature sets of data sets in the same subspace and different subspaces. To identify the most prevalent factor that affects the interest of the curriculum's literary components and then to conduct simulation testing and analysis. The proposed arithmetic has a particular accuracy, which is 8.25% greater than the conventional arithmetic, according to simulation findings. This outcome demonstrates in full how the enhanced arithmetic decreases the amount of records in the scanning database by grouping and compressing the database, hence lowering the scanning time and pruning before the connection process of Liu arithmetic. Classical literary works are without a doubt the most valuable resources to feed, edify, forge, and grow the spirit, soul, and personality of contemporary individuals throughout history and in all nations. Education through literature develops one's character, spirit, emotions, and aesthetic sense. The importance of reaffirming the significant place of literature education in contemporary national basic education cannot be overstated.

摘要

培养学生创造力、口头表达能力和精神成长的主要工具是文学阅读和写作。文学是一种艺术,通过语言的运用来唤起情感,表达作者对社会生活的理解和看法。阅读和写作文学作品有助于学生培养审美情趣和创造引人入胜的形象的能力,以及培养他们的精神和智慧。本研究提出了一种基于数据挖掘的最优设计方法,用于分析文学课程兴趣影响因素的关联规则。为了提高数据挖掘的频率和准确性,关联规则用于获取文学课程兴趣影响因素数据集之间的关联映射关系。然后使用粗糙集理论来区分同一子空间和不同子空间的数据集中的特征集。以识别影响课程文学部分兴趣的最常见因素,然后进行模拟测试和分析。根据模拟结果,与传统算法相比,提出的算法具有特定的准确性,准确率提高了 8.25%。这一结果充分表明,增强算法通过对数据库进行分组和压缩,减少了扫描数据库中的记录数量,从而降低了扫描时间,并在刘算法的连接过程之前进行修剪。古典文学作品无疑是滋养、陶冶、锻造和培养当代个人精神、灵魂和个性的最有价值的资源,贯穿历史和所有国家。通过文学进行教育可以培养人的品格、精神、情感和美感。文学教育在当代国民基础教育中的重要地位不容置疑。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/00c2/9481340/79bb94966c93/JEPH2022-1900509.007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/00c2/9481340/b67727b65be2/JEPH2022-1900509.001.jpg
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