Optimization of User Feature Extraction Algorithm Comprehensive Innovation System for Students in the Era of Computer Internet Big Data

Abstract

Ideological and political courses, as the main channel for cultivating students' world outlook, values, outlook on life and socialist core values, occupy an important position in the ideological and political education of colleges and universities. Aiming at the problems of traditional multimedia teaching methods, such as emphasizing skills and neglecting teaching, rigid use and lack of selectivity, this paper designs and implements an ideological and political teaching system based on big data analysis. The system consists of two parts: multimedia teaching software and computer big data recommendation. The multimedia teaching software realizes online teaching and resource management functions based on the B/S architecture. The big data recommendation subsystem recommends more suitable learning resources to users by collecting and analyzing user behaviors and extracting user characteristics. The function realization and performance test results show that the system has realized the teaching mode with students as the main body. It can not only effectively enhance the learning experience of students, but also support multiple people to learn online at the same time, which can effectively enhance students' learning initiative.