Design And Application Of Indoor Wooden Door Platform Based On Content Recommendation Algorithm

The output of indoor wooden door of China ranks first in the world.With the integration of informatization and industrialization,the indoor wooden door industry has ushered in a stage of rapid development and new opportunities.The sales model has changed from the traditional "offline sales" model to the "online drainage,offline service" model.However,as well as helping sales,the Internet also suffers from information overload.In this thesis,the content recommendation algorithm is applied to the online recommendation of indoor wooden doors,which is beneficial to improving the accuracy of online recommendation of indoor wooden doors,optimizing the personalized recommendation experience of indoor wooden door users,and achieving precise marketing of wooden door companies.The thesis analyzes the online recommendation function of indoor wooden doors,combining with the principles,advantages and disadvantages of common used recommendation algorithms,and it is clear that content recommendation algorithms can effectively meet the accuracy requirements of personalized recommendations of indoor wooden doors.This thesis applies the SSM(Spring,SpringMVC,MyBatis)framework to develop a personalized recommendation platform for indoor wooden doors.According to the basic principles of the content recommendation algorithm,the structural features of indoor wooden doors are extracted,and applies the Euclidean Distance to calculate the similarity between users and products.Through the ascending order of the similarity value to obtain the indoor wooden door recommendation result of the user.The main research contents and results of this thesis are as follows:(1)Analyzing from the comprehensive e-commerce,vertical e-commerce,official website and design platform four types of online sales drainage platform for indoor wooden door screening catalog and recommendation function,according to the principle of content recommendation algorithm and the relevant standards of indoor wooden doors,from categories,odeling,materials,functions,colors,styles,coatings and non-wood parts are used to extract all-round features of interior wooden doors to obtain a comprehensive and practical feature map of interior wooden doors.(2)A questionnaire survey on the purchase and recommendation needs of indoor wooden doors was carried out on users.According to the characteristics of low purchase frequency,high customer order value and weak professional knowledge,to sort out the requirements for personalized recommendation of indoor wooden doors,and develop a personalized recommendation platform for indoor wooden doors by using the SSM framework.The platform obtains characteristic interest vector of the user by recording user interaction behavior,and uses Euclidean Distance to calculate the similarity to obtain the user’s personalized recommendation list of indoor wooden doors.(3)Perform functional tests on the platform,invite 100 users to use the recommendation function constructed in this article and score the results.In the 10-minute test time,users used the content recommendation function to increase the shopping cart addition rate by 32.6%,laying a good foundation for the recommendation of indoor wooden doors.Collect user interest feature data,count 18 features with high user interest,and summarize 81 indoor wooden doors with sales promotion value.The platform data can provide a basis for the design and sales of wooden door companies.