Method and system for reading article recommendation based on big data

Abstract

The invention relates to a method and system for reading article recommendation based on big data. Based on a big data approach and according to reading behavior data of a large number of students, such as states and behavior characteristics during reading, and states and behavior characteristics after the reading, an article selection model is generated; input characteristic data of a student individual is collected; reading materials are recommended for the student individual in a targeted manner based on the article selection model; through correlation with expressions, environmental factors and so forth during student reading, the student's knowledge level and homework completion situations can be further correlated, so that influences of external factors and the student individual's study situations on the student reading can be obtained; and meanwhile, the student individual is also taken as a sample to generate the article selection model, so the more accurate article recommendation can be achieved. The invention also provides a recommendation result detection mechanism, wherein reading results of the student are detected; the detection result is used to reflect recommendation accuracy; cyclic iteration of the article section model can be carried out; and real-time effectiveness of the article recommendation can be ensured.

Description

technical field [0001] The present invention relates to data screening technology, more specifically, to a method for recommending reading articles based on big data, and a system for recommending reading articles based on big data. Background technique [0002] In an environment where there is no mandatory classification of information and materials, anyone can access any public information without barriers. Especially for the student group, it is easy to have access to information that is not suitable for their age, and relying on manual grading is limited by limited human resources and poor efficiency. And there is no effective measure to recommend to the student group after grading. [0003] On the other hand, among the materials and information suitable for students to read, including articles, reading materials, tutoring resources and other resources used to improve and cultivate students' abilities in various aspects, not all materials and information can effectively...

AI Technical Summary

Problems solved by technology

As a result, it is impossible to choose reading materials for individual students, which reduces students' acceptance of extracurricular reading materials.