TY - GEN
T1 - Extraction Method of Emotional Elements of Online Learning Text Information Based on Natural Language Processing Technology
AU - Song, Haolin
AU - Song, Dawei
AU - Zhen, Yankun
N1 - Publisher Copyright:
© 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2022
Y1 - 2022
N2 - The current methods of extracting emotional elements of text information generally adopt the principle of template matching, the algorithm is complex. Due to the limitations of the selected template, the network learning text information emotion elements cannot be comprehensively extracted, so the extraction accuracy and efficiency are low. In order to solve the above problems, this paper studies the emotional element extraction method of online learning text information based on natural language processing technology. Preprocess the online learning text information and find new words; Split the preprocessed text into sentences to generate transaction items; Frequent noun items are mined by association rules, irrelevant nouns are filtered by filtering algorithm, and the emotional elements of text information are extracted; Using the credibility analysis algorithm to judge the emotional polarity of text, and using the RNN neural network algorithm in natural language processing technology, the emotional elements of online learning text information are extracted. The test data show that the extraction time of the proposed feature extraction method is reduced by at least 35%, and the extraction accuracy of the method is improved to 80%, and the extraction result is more reliable.
AB - The current methods of extracting emotional elements of text information generally adopt the principle of template matching, the algorithm is complex. Due to the limitations of the selected template, the network learning text information emotion elements cannot be comprehensively extracted, so the extraction accuracy and efficiency are low. In order to solve the above problems, this paper studies the emotional element extraction method of online learning text information based on natural language processing technology. Preprocess the online learning text information and find new words; Split the preprocessed text into sentences to generate transaction items; Frequent noun items are mined by association rules, irrelevant nouns are filtered by filtering algorithm, and the emotional elements of text information are extracted; Using the credibility analysis algorithm to judge the emotional polarity of text, and using the RNN neural network algorithm in natural language processing technology, the emotional elements of online learning text information are extracted. The test data show that the extraction time of the proposed feature extraction method is reduced by at least 35%, and the extraction accuracy of the method is improved to 80%, and the extraction result is more reliable.
KW - Emotion extraction
KW - Emotional elements
KW - Natural language processing
KW - Neural network
KW - Online learning
KW - Text information
UR - http://www.scopus.com/inward/record.url?scp=85150996230&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-21161-4_41
DO - 10.1007/978-3-031-21161-4_41
M3 - Conference contribution
AN - SCOPUS:85150996230
SN - 9783031211607
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 542
EP - 552
BT - e-Learning, e-Education, and Online Training - 8th EAI International Conference, eLEOT 2022, Proceedings
A2 - Fu, Weina
A2 - Sun, Guanglu
PB - Springer Science and Business Media Deutschland GmbH
T2 - 8th EAI International Conference on e-Learning, e-Education, and Online Training, eLEOT 2022
Y2 - 9 July 2022 through 10 July 2022
ER -
