
E-Iearning is the process of learning., educating, or training using web-based technologies. With the extensive use of such means, a tremendous amount of data are generated. The traditional methods of manual features engineering to collect, manage and process those data are very limited and time-consuming. Deep learning is one of the modern approaches that could automate this process in order to achieve effective smart e-learning. In this paper., we aim to introduce our personalized e-learning model that associate deep learning with process mining., in order to provide the learners with learning resources that fit their individual preferences., after giving an overview about both e-learning as an online educational system, and deep learning as a broader family of artificial intelligence.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 21 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
