Learning resource recommendation system based on user portrait

Abstract

The invention requests to protect a learning resource recommendation system based on user portraits, which is used for accurately and personally recommending course resources and comprises four levels, namely a data acquisition layer, a data processing layer, a model algorithm layer and a personalized service layer. The method comprises the following steps that: basic information of a user, browsing behavior information of a website, viewed content information and evaluation communication information are collected; data is classified and gathered through the collected information, a corresponding label library is established for each learner, resources in the label libraries are associated, personal portraits are established for the current learners along with continuous increase of the access frequency of the users, and meanwhile group portraits are also established. A course resource list obtained by a recommendation algorithm is recommended to the learners. According to the method,the feedback and click records given by the learners are recorded, so that better personalized service and accurate recommendation can be realized, the resource searching time of the learners can be saved, and meanwhile, the learning condition of the learners on knowledge can be known in a portrait mode.

Description

technical field [0001] The invention belongs to the field of user portraits, in particular to a learning resource recommendation system based on user portraits; Background technique [0002] In the era of Internet pan-information, data and information from all walks of life are growing exponentially, and there are more and more data on the Internet; while the Internet brings us convenience, it also brings us troubles. We must not Don’t spend more time looking for the information you need. From the perspective of time, we have increased our search costs. If we know keywords, we can find them through search engines; if the information users need cannot be found through keywords Search, this time we need our recommendation method to recommend related information for users; [0003] With the popularization of Internet education, a large number of educational courses have emerged. For example, Coursera has opened various courses in more than 22 fields, and has collected more tha...

AI Technical Summary

Problems solved by technology

[0002] In the era of Internet pan-information, data and information from all walks of life are growing exponentially, and there are more and more data on the Internet; while the Internet brings us convenience, it also brings us troubles. We must not Don’t spend more time looking for the information you need. From the perspective of time, we have increased our search costs. If we know keywords, we can find them through search engines; if the information users need cannot be found through keywords Search, this time we need our recommendation method to recommend related information for users;

[0003] With the popularization of Internet education, a large number of educational courses have emerged. For example, Coursera has opened various courses in more than 22 fields, and has collected more than 150,000 episodes of high-quality course resources; there are massive resources on the In

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