ABSTRACT. This paper aims to identify the degree to which social media influence or support the learning process among students. The research was complex, involving three international panels, comprising students from Poland, China and Romania. Although intercultural differences between the three countries are evident, the attitudes and perceptions of the usefulness of social media in learning activities tend to be homogeneous, revealing not just the extensive use of this worldwide phenomenon amongst young people, but also its significance. Social media have impacted greatly on the way people relate, both positively and negatively. This research focuses on the analysis of the use of social networking in the process of training and self-training in youth education.
Multilabel classification is a key research topic in the machine learning field. In this study, the author put forward a two/two-layer chain classification algorithm with optimal sequence based on the attention mechanism. This algorithm is a classification model with a two-layer structure. By introducing an attention mechanism, this study analyzes the key attributes to achieve the goal of classification. To solve the problem of algorithm accuracy degradation caused by the order of classifiers, we adopt the OSS (optimal sequence selection) algorithm to find the optimal sequence of tags. The test results based on the actual dataset show that the ATDCC-OS algorithm has good performance on all performance evaluation metrics. The average accuracy of this algorithm is over 80%. The microaverage AUC performance reaches 0.96. In terms of coverage performance, its coverage performance is below 10%. The comprehensive result of single error performance is the best. The loss performance is about 0.03. The purpose of the ATDCC-OS algorithm proposed in the study is to help improve the accuracy of multilabel classification so as to obtain more effective data information.
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