Online Curriculum Management of Higher Education Under Mobile Platform

Abstract

The web crawler technology obtains data from experiment such as learner-curriculum interaction data, course content data and knowledge map. After crawling the data from the network, the data cleaning work is carried out, which is to analyse, sort, calculate and edit various raw data. Finally, the processed data is stored as data files, and the collection of relevant basic data sets of curriculum recommendation is completed. In this paper, the online curriculum management system of higher education based on the design of mobile platform adopts the recommendation model of knowledge map enhancement Ripple_mlp and its improved model Rippk_mlP+. Firstly, the common algorithms of curriculum recommendation are analyzed, and the source of ideas for the construction of new model is described. Then, the scenario of curriculum recommendation is defined in abstract, and the overall framework of the model is summarized, and the specific contents of the four parts of the model are described in detail. Then, based on the feature of "one to many" in the course recommendation area, the paper introduces Co-net into Ripple_mlp model to optimize it. Finally, the optimization method of the model is introduced.