Design And Implementation Of Intelligent Recommendation System Of Open Class VOD Platform

Today,the majorcolleges and universities have been actively involved in the construction of their own video sharing platform,video open class has gradually become one of the majority of users learning platform.However,because of these video open class information retrieval rely on the user to retrieve,and in the massive resources in the search of interesting videos,consuming a lot of time,energy and other costs.In order to improve the efficiency in the use of open course resources,shorten the path of user video on demand,improve user demand interest,this paper on the basis of original video on demand platform,the user behavior data modeling,build a with personalized recommendation,can shorten the video on demand(VOD)size,higher ordering efficiency of intelligent recommendation system,so as to achieve the user interest mining,take the initiative to the user recommend related courses and video of the target.Firstly,theproposed technology,such as personalized recommendation technology in Recommendation Algorithm Based onassociation rules and recommendation algorithm based on content and collaborative filtering algorithms to find user similarity,using WEB server and JS script capture user behavior,and modeling,classification of users' interest for recommended,finally to Hadoop technology based system,the overall architecture design in video on demand platform intelligent recommendation system of open class,including the technical architecture,logical architecture design objectives and constraints of the system and the system,and then the design and implementation of all aspects of the system,such as the design and implementation of user behavior,user behavior modeling,data acquisition real-time recommendation the interface layer,realization,finally through the test of intelligent recommendation system design and application of effective.Through the test,in the open class video on demand platform intelligent recommendationsystem,user video on demand(VOD)path relationship 11.65 seconds,video playback,the average completion degree increased 26.12%,saving the user time,improve the video open class resource utilization rate,better play the video open class of utility.