Remote education resource recommendation method and device

Abstract

The invention discloses a remote education resource recommendation method and device. The remote education resource recommendation method includes steps that (1) calculating according to user information to obtain interest level R of a user for education resource, and storing in a user interest table; (2) calculating the user-resource grading rate T of the user according to the user information; (3) comparing the user-resource grading rate T with a specified threshold VT, if the user-resource grading rate T is smaller than or equal to the specified threshold VT, forecasting the interest level of the user for the education resource, filling a forecast value as the interest level R, storing in the user interest table, and recommending the education resource which the user is interested in according to the user interest table; if the user-resource grading rate T is larger than the specified threshold VT, directly recommending the education resource which the user is interested in according to the user interest table. By means of the technical scheme, the remote education resource recommendation method and device are capable of precisely recommending resource for the user and solving the cold boot problem of a collaborative filtering technology for a new established educational website.

Description

technical field [0001] The invention relates to the field of information processing, in particular to a method and device for recommending distance education resources. Background technique [0002] In recent years, the number of educational resources on the Internet has increased dramatically, and users spend more and more time searching for the educational resources they need, resulting in the "information overload phenomenon". In order to reduce the cost for users to find the required educational resources, educational resource recommendation technology emerged as the times require. Educational resource recommendation technology generally automatically recommends educational resources that may be of interest to users by analyzing user behavior (for example, scoring educational resources). Collaborative filtering technology is one of the most widely used technologies in educational resource recommendation systems. Its basic idea is to find a user group (neighborhood user...

AI Technical Summary

Problems solved by technology

However, many users are unwilling to rate resources, or the ratings are relatively random, which makes the system unable to produce accurate recommendation results

[0003] In addition, collaborative filtering technology has the technical defect of "cold start"

For newly established educational websites, the ratio of educational resources being browsed and rated is low, and it is difficult for the recommendation system to generate a target user’s neighbor user set, and the recommendation results are not satisfactory

For newly launched educational resources, since there is no user's browsing or evaluation history, the system cannot attribute them to the interest range of neighboring user sets, and thus cannot recommend the latest resources to users

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