Using the beta distribution technique to detect attacked items from collaborative filtering

Hsu, Ping-Yu; Chung, Jui Yi; Liu, Yu Chin

doi:10.3233/ida-194935

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…Hsu et al solved the problem of data sparsity by principal component analysis. However, this kind of algorithm using matrix dimension reduction not only takes time but also loses some effective scoring information [ 14 ]. Paleti et al put forward a trust calculation algorithm based on project level, topic level, and user outline level, but the calculation of trust is limited by the number of users' scores, so this method needs further improvement [ 15 ].…”

Section: Related Workmentioning

confidence: 99%

[Retracted] Design and Implementation of Mental Health Consultation System for Primary and Secondary School Students Based on Credibility Matching Model

2022

Journal of Environmental and Public Health

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Primary and secondary schools have the enormous responsibility of developing talent over a hundred years, and they should not only be concerned with the moral, ideological, and cultural development of teenagers but also with their mental well-being. We need to start by making the external environment better, provide in-depth psychological counseling, and support students as they work to continually increase their psychological adaptability in order to promote the healthy development of their personalities. As the epidemic situation in China has now stabilized into a normal state of prevention and control, it is imperative to provide primary and secondary school students with mental health education. In light of this context, this paper develops a browser-server network architecture-based consultation system for the mental health of students in primary and secondary schools. It eliminates the conventional booking mode and substitutes credibility as the characteristic programming parameter. The performance of the original system is improved by the reliability model the most when the parameter is set to 0.2, and the recovery rate rises by 1.32 percent. Compared to the original reliability model, which improved the system’s F value performance by 0.83 percent, the accuracy rate only declines by 0.68 percent while F rises by 0.37 percent. This research is crucial for creating an information campus and raising the standard of psychological counseling.

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Section: Related Workmentioning

confidence: 99%

[Retracted] Design and Implementation of Mental Health Consultation System for Primary and Secondary School Students Based on Credibility Matching Model

2022

Journal of Environmental and Public Health

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“…Strategy II is used to synthesize the group matrix before decomposing the user scoring matrix. Strategy III adds weight to user characteristics before user scoring and finally decomposes the group score [ 9 ]. Song and others proposed a matrix decomposition model to add group information features.…”

Section: Related Workmentioning

confidence: 99%

Data Mining Method of Intelligent Market Management Based on Collaborative Recommendation Algorithm

Wu¹,

Wang²,

Cai³

2022

Computational Intelligence and Neuroscience

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In order to solve the problems of low coverage and accuracy and large mean absolute error and root mean square error when traditional algorithms recommend market management data, this paper proposes an intelligent market management data mining method based on a collaborative recommendation algorithm. According to the preference value of the attribute characteristics of market management data, predict and score the attribute characteristics of market management data; use data mining technology to preprocess the information of market management data, combined with the design of collaborative filtering recommendation algorithm; and realize the collaborative filtering recommendation of market management data. With 50 recommendations, AGCAN improves the accuracy of MovieLens-1M by 43.81%, 5.43%, 1.87%, 0.42%, and 1.67%, respectively, compared with the five benchmark algorithms. For MovieLens-100K, compared with the five benchmark algorithms, AGCAN improves the accuracy by 51.17%, 10.52%, 3.37%, 0.1%, and 0.30%, respectively. Compared with the five benchmark algorithms, Amazon-baby and AGCAN have improved the accuracy by 34.37%, 28.12%, 31.25%, 29.1%, and 3.12%, respectively. The algorithm proposed in this paper uses a graph neural network to mine useful information between users and projects, but it lacks the use of other personalized interest information of users, such as user interest, user purchase time, and so on.

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“…The curriculum implementation evaluation is the process of implementing the scheduled plan, and the measurement standard is the degree of achievement of teaching objectives. From the political point of view, the curriculum implementation evaluation is regarded as the interest competition between groups, and different competitive relationships maintain different attitudes towards the curriculum implementation evaluation [2,6,20]. From the culture perspective, curriculum implementation evaluation is regarded as cultural regeneration, and curriculum implementation evaluation is the process of promoting teachers to think over teaching arrangements.…”

Section: Qualitative Evaluation Of Course Implementation Based On Col...mentioning

confidence: 99%

Evaluation of Curriculum Implementation Effectiveness of Higher Vocational Education Based on Collaborative Filtering Algorithm

Wang,

2023

SCPE

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The conventional evaluation method for the effectiveness of curriculum implementation mainly focuses on the complete orientation analysis of students’ curriculum content, which does not reflect the value of the educational curriculum and affects the effectiveness of evaluation. Therefore, an evaluation method of curriculum implementation effectiveness of higher vocational education based on a collaborative filtering algorithm is designed. Identify the practical focus of evaluating the implementation of the higher vocational education curriculum and discover the educational curriculum’s significance. Qualitative evaluation of curriculum implementation degree based on collaborative filtering algorithm, find out the hidden characteristics of curriculum implementation evaluation to effectively evaluate higher vocational education curriculum implementation. Using case analysis, it is verified that the method is more effective and can be applied in real life.

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Using the beta distribution technique to detect attacked items from collaborative filtering

Cited by 6 publications

References 24 publications

[Retracted] Design and Implementation of Mental Health Consultation System for Primary and Secondary School Students Based on Credibility Matching Model

[Retracted] Design and Implementation of Mental Health Consultation System for Primary and Secondary School Students Based on Credibility Matching Model

Data Mining Method of Intelligent Market Management Based on Collaborative Recommendation Algorithm

Evaluation of Curriculum Implementation Effectiveness of Higher Vocational Education Based on Collaborative Filtering Algorithm

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