2021
DOI: 10.1155/2021/9977736
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Abnormal Access Behavior Detection of Ideological and Political MOOCs in Colleges and Universities

Abstract: In many colleges and universities, MOOCs have been applied in many courses, including ideological and political course, which is very important for college students’ ideological and moral education. Ideological and political MOOCs break the limitations of time and space, and students can conveniently and quickly learn ideological and political courses through the network. However, due to the openness of MOOCs, there may be some abnormal access behaviors, affecting the normal process of MOOCs. Therefore, in thi… Show more

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Cited by 12 publications
(13 citation statements)
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References 16 publications
(15 reference statements)
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“…Hong et.al. [13], present a strategy for detecting unusual access patterns in IP-MOOCs in institutions. e model for detecting net activities is built using DL to distinguish between normal and abnormal network behavior to detect anomalous access network behavior.…”
Section: Related Workmentioning
confidence: 99%
“…Hong et.al. [13], present a strategy for detecting unusual access patterns in IP-MOOCs in institutions. e model for detecting net activities is built using DL to distinguish between normal and abnormal network behavior to detect anomalous access network behavior.…”
Section: Related Workmentioning
confidence: 99%
“…[7]. The development and utilization of political theory teaching resources in colleges and universities are of positive significance to improve students' comprehensive quality [8]. The unified curriculum is highly abstract and logical, and it also has a certain lag, resulting in classroom teaching activities being usually mainly taught by teachers and students being more passive when facing the curriculum, and it is difficult to integrate the theory with practice [9].…”
Section: Introductionmentioning
confidence: 99%
“…Hong et.al (2021) [13], presents a strategy for detecting unusual access patterns in IP-MOOCs in institutions. The model for detecting net activities is built using DL to distinguish between normal and abnormal network behavior to detect anomalous access network behavior.…”
Section: Related Workmentioning
confidence: 99%