Association Rules Mining for STO Dataset of HSES Knowledge Portal System

Miri, Santosh Kumar; Sahu, Neelam; Miri, Rohit; Tandan, S. R.

doi:10.1007/978-981-15-5400-1_60

Cited by 1 publication

(1 citation statement)

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“…According to the survey, it turns out that the husband usually buys diapers after a wife gives birth, while men usually buy beer for themselves in the United States. As a result, beer and diapers were put in the same place to facilitate customers and increase sales [21].…”

Section: Association Rulesmentioning

confidence: 99%

Research on Personalized Recommendation Methods for Online Video Learning Resources

Chen

Deng

2021

Applied Sciences

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It is not easy to find learning materials of interest quickly in the vast amount of online learning materials. The purpose of this study is to find students’ interests according to their learning behaviors in the network and to recommend related video learning materials. For the students who do not leave an evaluation record in the learning platform, the association rule algorithm in data mining is used to find out the videos that students are interested in and recommend them. For the students who have evaluation records in the platform, we use the collaborative filtering algorithm based on items in machine learning, and use the Pearson correlation coefficient method to find highly similar video materials, and then recommend the learning materials they are interested in. The two methods are used in different situations, and all students in the learning platform can get recommendation. Through the application, our methods can reduce the data search time, improve the stickiness of the platform, solve the problem of information overload, and meet the personalized needs of the learners.

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Section: Association Rulesmentioning

confidence: 99%