Approach to Processing of Data from Social Networks for Detecting Public Opinion On Quality of Educational Services

被引：0

作者：

Khomonenko, A. D. ^{[1
]}

Dashonok, V. L. ^{[1
]}

Ivanova, K. A. ^{[1
]}

Kassymova, D. T. ^{[2
]}

机构：

[1] Emperor Alexander I St Petersburg State Transport, St Petersburg, Russia

[2] Kazakh Natl Res Tech Univ KI Satpayev, Alma Ata, Kazakhstan

来源：

PROCEEDINGS OF 2017 XX IEEE INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND MEASUREMENTS (SCM) | 2017年

关键词：

quality of educational services; latent-semantic analysis; machine-generated texts; quality;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

An approach is proposed to identify public opinion on the basis of large data extracted from social networks, including: latent-semantic analysis, identification of computer-generated texts, automatic classification of text fragments and identification of public opinion based on Mamdani's fuzzy inference algorithm. Examples are given of assessing the semantic proximity of documents, the classification of documents based on the method. The indicators for assessing public opinion on the evaluation of the quality of educational services are substantiated.

引用

页码：737 / 739

页数：3

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