A method to determine the accuracy of the automatic page-turning navigation function

Commonly, learners need to find one other page that they read exploring those that correlated with this page in terms of potential interest or knowledge. However, it is hard to do with online learning materials. In that case, automatic page-turning navigation can recommend learning with pages by algorithms designed to calculate the relevance between pages. However, currently, when performing automatic page-turning navigation, it is mainly calculated by the click-through rate of page kin as well, and does not take into account the knowledge content on the page. In this study, a natural language analysis method based on morphological analysis is designed to detect the accuracy of the current automatic page-turning navigation by calculating the relevance of the knowledge contained within a page.