Evaluation of Web-Based Teaching Based on Machine Learning and Text Emotion

Authors

  • Lifang Wang Physical Education College Xi’an Physical Education University, Xi’an, Shaanxi 710068, China

Abstract

In the era of big data, the analysis of text sentiment is an effective means of mining text data, which has strong practicability. In this paper, the author analyzes the evaluation of web-based teaching based on machine learning and text emotion The core of the machine learning method is the selection of an effective feature combination and the use of a classifier to classify emotion. The method of evaluating teachers’ teaching quality by means of a network saves data processing time, makes the evaluation more comprehensive, gives a more detailed evaluation of the data, and indicates teachers’ actual teaching situation more fairly and impartially. This paper introduces the main technologies used in the system, and conducts a detailed demand
analysis for each subsystem, designs important modules and technologies such as a database and, finally, it summarizes the system design process and its shortcomings . At the same time, combining word vector and emotion, a vector matrix and hash table index are constructed, which significantly improve the efficiency of the model. This data preprocessing method can be widely used in other natural language processing tasks.

Keywords: Machine Learning; Text Emotion; Database; Hidden Markov models; Deep semantic objects

Cite As

L. Wang, "Evaluation of Web-Based Teaching Based on Machine Learning and Text Emotion", Engineering Intelligent Systems, vol. 27 no. 3, pp. 111-119, 2019.



Downloads

Published

2019-09-01

Issue

Vol. 27 No. 3 (2019): International Journal of Engineering Intelligent Systems

Section

General Submission

License

The submission of a paper implies that, if accepted for publication, it will not be published elsewhere in the same form, in any language, without the prior consent of the publisher. Before publication, authors are requested to assign copyright to CRL Publishing Ltd. This allows CRL to sanction photocopying, and to authorize the reprinting of issues or volumes according to demand. Authors' traditional rights will not be jeopardized by assigning Copyright in this way, as they retain the right to reuse the material following publication, and to veto third-party publication.