A Summarization Generation Method for E-Courseware on the Internet Platform

With the increase of various online learning platforms, lots of electronic coursewares (e-courseware) are uploaded to the Internet platform for users' learning and sharing. Constructing the summarization for e-courseware through extracting the content of e-courseware is of great importance for users to select and utilize e-courseware for the self-learning process. But the information extraction algorithm for e-courseware has not been fully studied on the Internet Platform. This paper proposes a new method for extracting courseware information based on automatic summarization, and then applies it to generate automatically the summarization covering the knowledge content of e-courseware on the Internet platform. Based on the analysis of e-courseware structure, the method uses the extractive and abstractive automatic digest algorithm to deal with the text of a single slide, and then calculates the similarity of two sentences outputted by the two algorithms to determine the final key information, finally organizes the summarization of e-courseware based on the extracted key information. The experimental results show that the algorithm has a good performance in the summarization and generalization of text information for e-coursewares, which is conducive to the generation of learning notes for users so as to quickly understand the content of e-courseware.