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Education big data text analysis method based on APSO-LSTM network

A text analysis and big data technology, which is applied in the field of text analysis of educational big data based on APSO-LSTM network, can solve the problem that text data is not well utilized and analyzed

Pending Publication Date: 2021-10-15
BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Every year, a large number of learners participate in these large-scale online courses, resulting in a large amount of text comment data on courses and teachers, but these text data are not well utilized and analyzed to further understand their understanding of course content and Perceptions of Educational Quality, Improving the Quality of the Curriculum

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  • Education big data text analysis method based on APSO-LSTM network
  • Education big data text analysis method based on APSO-LSTM network
  • Education big data text analysis method based on APSO-LSTM network

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Embodiment 1

[0036] combine figure 1 as shown, figure 1 A flow chart of an educational big data text analysis method based on the APSO-LSTM network provided by the present invention. The present embodiment provides a method for analyzing texts of educational big data based on the APSO-LSTM network, comprising steps:

[0037] Step S1: collecting raw data to form a data set, the data set includes a first raw data set and a second raw data set;

[0038] Step S2: Preprocessing the first original data set to obtain a text data set;

[0039] Step S3: use the Skip-Gram model to train the text data set to obtain a word vector set;

[0040] Step S4: Label the word vector set with emotion labels to form a sample data set, which includes the training set;

[0041] Step S5: using the training set to train the APSO-LSTM network model to obtain a text sentiment analysis model;

[0042] Step S6: After inputting the second original data set into the text sentiment analysis model, saving the classific...

Embodiment 2

[0048] continue to combine figure 1 and figure 2 as shown, figure 2 A kind of APSO algorithm flowchart provided by the present invention, image 3 A block diagram of a Skip-Gram provided by the present invention, Figure 4 A flowchart of Word2Vec word clustering keywords provided by the present invention.

[0049] The present embodiment provides a method for analyzing texts of educational big data based on the APSO-LSTM network, comprising steps:

[0050] Step S1: collecting raw data to form a data set, the data set includes a first raw data set and a second raw data set.

[0051]In step S1, the data set includes a first original data set and a second original data set, and the first original data set and the second original data set are different data sets. Use the first original data set to train the APSO-LSTM network model to obtain the text sentiment analysis model, then substitute the second original data set into the text sentiment analysis model to obtain the key...

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Abstract

The invention discloses an education big data text analysis method based on an APSO-LSTM network, and the method comprises the steps: collecting original data, and forming a data set which comprises a first original data set and a second original data set; preprocessing the first original data set to obtain a text data set; training the text data set by using a Skip-Gram model to obtain a word vector set; labeling the word vector set with an emotion label, forming a sample data set, wherein the sample data set comprises a training set; training an APSO-LSTM network model by using the training set to obtain a text sentiment analysis model; after the second original data set is input into the text sentiment analysis model, storing the classification results of the original data in the second original data set as text files; training the text file by using a Word2Vec model to obtain keywords of positive and negative emotional tendencies; and generating an emotion analysis report according to the keywords, so that a basis is provided for improvement of network online education.

Description

technical field [0001] The invention relates to the technical field of text data mining, in particular to a text analysis method for educational big data based on an APSO-LSTM network. Background technique [0002] With the rapid development of information technology, especially from the Internet to the mobile Internet, the way of living, working and learning across time and space has been created, and the way of knowledge acquisition has undergone fundamental changes. Teaching and learning can not be restricted by time, space and location conditions, especially during the epidemic period, online teaching has been implemented throughout the country, and knowledge acquisition channels are flexible and diverse. [0003] So student feedback is crucial to assessing the effectiveness of a course of study. With the increase of educational institutions, many students are fascinated by online learning portals by offering free courses for free. Every year, a large number of learner...

Claims

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Application Information

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IPC IPC(8): G06F40/205G06F16/35G06N3/04G06N3/08
CPCG06F40/205G06F16/35G06N3/08G06N3/044
Inventor 黄先开张佳玉张跃
Owner BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY