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Full-Text Articles in Social and Behavioral Sciences
Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin
Hybrid Translation And Language Model For Micro Learning Material Recommendation, Jiayin Lin
Faculty of Engineering and Information Sciences - Papers: Part A
As an emerging pedagogy, micro learning aims to make use of people’s fragmented spare time and provide personalized online learning service, for example, by pushing fragmented knowledge to specific learners. In the context of big data, the recommender system is the key factor for realizing the online personalization service, which significantly determines what information will be fmally accessed by the target learners. In the education discipline, due to the pedagogical requirements and the domain characteristics, ranking recommended learning materials is essential for maintaining the outcome of the massive learning scenario. However, many widely used recommendation strategies in other domains showed …
From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen
From Ideal To Reality: Segmentation, Annotation, And Recommendation, The Vital Trajectory Of Intelligent Micro Learning, Jiayin Lin, Geng Sun, Tingru Cui, Jun Shen, Dongming Xu, Ghassan Beydoun, Ping Yu, David Pritchard, Li Li, Shiping Chen
Faculty of Engineering and Information Sciences - Papers: Part B
The soaring development of Web technologies and mobile devices has blurred time-space boundaries of people’s daily activities. Such development together with the life-long learning requirement give birth to a new learning style, micro learning. Micro learning aims to effectively utilize learners’ fragmented time to carry out personalized learning activities through online education resources. The whole workflow of a micro learning system can be separated into three processing stages: micro learning material generation, learning materials annotation and personalized learning materials delivery. Our micro learning framework is firstly introduced in this paper from a higher perspective. Then we will review representative segmentation …
Pairwise-Based Hierarchical Gating Networks For Sequential Recommendation, Kexin Huang, Ye Du, Li Li, Jun Shen, Geng Sun
Pairwise-Based Hierarchical Gating Networks For Sequential Recommendation, Kexin Huang, Ye Du, Li Li, Jun Shen, Geng Sun
Faculty of Engineering and Information Sciences - Papers: Part B
The sequential pattern behind users’ behaviors indicates the importance of exploring the transition relationships among adjacent items in next-item recommendation task. Most existing methods based on Markov Chains or deep learning architecture have demonstrated their superiority in sequential recommendation scenario, but they have not been well-studied at a range of problems: First, the influence strength of items that the user just access might be different since not all items are equally important for modeling user’s preferences. Second, the user might assign various interests to certain parts of items, as what often attracts users is a specific feature or aspect of …