Abstract

In order to meet the need of individualized learning, the current network teaching platform all bring in recommendation system, including the recommendation of learning resources, the recommendation of task and exercise, etc. Problems like outdated datum or sparse datum still exist in teaching platform recommendation. Take task recommendation system of computer courses as an example, the computer knowledge updates quickly. The old knowledge will be out of date in two to three years. Another case is that, when the website was put into use, as the website traffic is quite low, the datum of task finished by the students are quite little. Both of those two cases can cause sparse datum of task system in network teaching platform. In order to solve this problem, this article tries to apply transfer learning into network teaching recommendation system, and verify its feasibility through experiment.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.