| With the popularity of 5g network,the development of the Internet era is further accelerated,and the amount of information on the network is increasing day by day.How to quickly screen out effective information in the era of information explosion has become the key to affect the user experience.The recommendation system uses information filtering technology to push the content of interest to users by analyzing users’historical behavior.Especially in the field of e-commerce,it can not only help users buy goods quickly and improve the user experience,but also play a great role in improving the commodity conversion rate of merchants,and can solve the problem of user loss caused by too much information.As one of the key technologies of recommendation system,collaborative filtering technology still has problems in cold start and data sparsity,but it can find user interest and deal with unstructured data.In this paper,two collaborative filtering algorithms are used to realize the recommendation system of self-study room:This paper studies and analyzes the collaborative filtering recommendation system,and uses the collaborative filtering algorithm to realize the self-study room recommendation according to whether the item category is fuzzy.The collaborative filtering algorithm used in this paper is based on the user’s preference for the self-study room attribute.The calculation of correction factor is mainly introduced to balance the interaction between the user’s self-study room attribute preference and the self-study room similarity.The demand analysis of this paper mainly introduces the design and implementation of the self-study room recommendation system based on collaborative filtering from the aspects of user experience,outline design,detailed design and system test.It will introduce the system development framework SSM,search engine es and recommendation system framework mahout.In terms of functional modules,it mainly expounds the self-study room reservation module,search module and self-study room recommendation module.The self-study room system mainly realizes the reservation of seats in the self-study room and the purchase of products in the self-study room.Through this system,users can effectively select appropriate self-study rooms and products,improve user experience,help users realize online remote seat reservation,and improve the conversion rate of merchants.The data used in this system is the transaction scoring data of actual users in offline stores,In the absence of relevant products,it is of practical significance for the current situation of the industry. |
