基于AI的自主规划考研网站的设计与实现

Abstract

This paper mainly introduces the design and implementation of self planning postgraduate entrance examination website which combines ai artificial intelligence technology with web application form. On the student side, it can not only query information, but also have forum, open class, live broadcast module and other functions. In addition, the recommendation system is added to enable students to find the information they need faster. Through AI yellow detection and facial expression recognition, opencv is used to calculate the proportion of skin in the picture, and PIL is used to add watermark in the image to create health for students In the open class module, knbaseline algorithm is used, that is, the collaborative filtering algorithm based on articles and baseline rating is used. Tensorflow training data is used in the sharing center, and the content-based recommendation algorithm is used according to the user's requirements Behavior, including browsing, like, comments, forwarding and other characteristic data, to calculate the students' preferences and characteristics, and finally recommend the post. For the postgraduate entrance examination students, each person has his own circle of friends, and the administrator can directly enter the background of the website background to edit and update in real time. Different administrators have different permissions. This website has been successfully deployed on windows server2012 R2 server, running stably, achieving the expected goal, and has certain practical value.