Intelligent recommendation method and system for local educational institutions based on user similarity

Abstract

An intelligent recommendation method and system for local educational institutions based on user similarity are provided. The method comprises the following steps: an authentication module of the server verifies the user identity; the information obtaining module of the server obtains the education information of the user, the education information comprises: a school, an educational institution and a profession; the verification module verifies the authentication of the educational institution; the information obtaining module obtains the identity and educational information of the user participating in the educational institution, and the curriculum of the user in the educational institution; the screening and sorting module divides the educational institution into a first sequence and asecond sequence according to the user identity and educational information; the pushing module pushes an educational institution of a user whose educational information similarity degree exceeds a preset threshold value to the user in a manner of a first sequence and a second sequence. The method further comprises the following steps: the information obtaining module obtains the number of coursesof a user in an educational institution; the information obtaining module obtains the attendance rate of the user to the course; the information obtaining module server obtains the satisfaction degree of the user to the educational institution.

Description

technical field [0001] The invention relates to the field of education, in particular to an intelligent recommendation method and system for local educational institutions based on user similarity. Background technique [0002] With the popularization of the Internet, various local education resources have become more abundant. How to find suitable local educational resources according to the needs of users has become a very practical problem. [0003] Traditional educational resource recommendations are mostly based on word of mouth or leaflets. With the advent of the information age, a variety of educational institutions and models have sprung up one after another. For ordinary users, how to identify suitable educational resources is not a small problem. Automatic recommendation based on big data is the fundamental way to solve this problem. Existing recommendation technologies are generally based on collaborative recommendations from friends or similarity recommendatio...

AI Technical Summary

Problems solved by technology

Existing recommendation technologies are generally based on collaborative recommendations from friends or similarity recommendations based on content understanding, which may not necessarily meet the needs or expectations of users. Users need to identify suitable educational institutions and courses, which takes a lot of time and even money.

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