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Personalized recommendation method based on user data of on-line courses

A technology for user data and recommendation methods, which is applied in electrical digital data processing, special data processing applications, instruments, etc., and can solve problems such as cold start of users with too little information

Active Publication Date: 2015-12-09
BEIJING JUDAOYOUDA NETWORK TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Apply the traditional collaborative filtering recommendation method to the personalized feedback of user learning on the online course learning platform, and solve the cold start problem of users with too little information

Method used

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  • Personalized recommendation method based on user data of on-line courses
  • Personalized recommendation method based on user data of on-line courses
  • Personalized recommendation method based on user data of on-line courses

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Experimental program
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Embodiment Construction

[0039] The present invention will be further described below in conjunction with the drawings and embodiments.

[0040] The present invention is based on the integration and processing of the original learning data, predicts the N courses with the highest error rate from the user's real error rate and the similarity between courses, performs weighted voting to calculate the recommendation weight of the extracurricular challenge topic under the corresponding label mapping, and obtains the recommendation List.

[0041] Take an online programming learning website as an example for further explanation. The main steps are as follows:

[0042] 1. Preprocessing of the original user data to obtain the user's error list: extract the original learning records from the database, and analyze the user's submitted operation data (cid, uid, active_type, active_text, time)

[0043] The parameters represent: cid: the unique id of the course, uid: the unique id of the learning user, active_type: the ty...

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Abstract

The invention discloses a personalized recommendation method based on user data of on-line courses. The method comprises following steps of: 1), establishing label mapping relations among courses, labels and titles; 2), calculating an error rate list ET of a user to courses by a course recommendation system according to learning records of the user; 3), generating error lists of all courses according to the list ET and calculating the similarity between two courses according to error lists of courses; and 4), as for each user, calculating prediction weight of error rate of each course of the user according to similarity; calculating recommendation weight of each label according to mapping relations and prediction weight of error rate; calculating recommendation weight of each title according to mapping relations and label recommendation weight and then generating a recommendation list for the user according to recommendation weight of titles. The personalized recommendation method based on user data of on-line courses not only helps to solve a cold start problem but also actively attracts attention of the user in order to improve learning motivation.

Description

Technical field [0001] The present invention relates to the field of personalized prediction and recommendation. It predicts error peak courses based on the historical learning data of online course website users, and performs personalized recommendations for expanding learning content under corresponding label mapping, such as challenge topics. Specifically, it is a personalized content recommendation method based on online course user data. Background technique [0002] As one of the most popular learning methods at present, online course learning websites provide a wide range of resources and open platforms for learning users to a certain extent, but there are also some obvious drawbacks in this current learning method: 1. Accompanying learning It is easy to make users vaguely judge their own learning situation; 2. The expansion of resources and information will make users blindly blind to the content to be learned; 3. Provide undifferentiated course content for users of diffe...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 周英华张茜杨斌俞昊然孙广中
Owner BEIJING JUDAOYOUDA NETWORK TECH
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