Design And Implementation Of Recommendation System Based On House Rental Data

The rapid development of the Internet and related information technology industries has enabled more and more technology products and services to connect to the Internet.Ziroom,Anjuke,5i5 j.com,Beike and other network platforms collect and publish the housing rental information of each city on the Internet,which greatly facilitates the acquisition of housing rental information and brings a lot of data.The huge amount of data has caused us to be troubled by the screening of data,which has seriously reduced people's efficiency in obtaining effective information.In order to help users quickly find the data content that meets the user's own needs in the massive housing data published by different platforms,this paper has carried out research,designed and implemented the housing rental data recommendation system.The paper introduces the research status and related principles and theories of the recommendation system at domestic and international,and explains in detail the other related technologies used in the design and implementation process of the system.Based on the analysis of the specific use scenarios and usage environment,the overall structural design of the recommendation system and the detailed design of each sub-module are completed.On the basis of detailed analysis of each housing rental website and its data content,the reptile tool is used to realize the data integration of the major housing rental websites and platforms,and finally the acquisition of the recommended objects and recommended data is completed.The user interest preference model is established by adopting the modeling method based on K-Means clustering algorithm and using the contour coefficient to judge and select the more reasonable clustering.The recommendation of the data is completed by using the gray correlation analysis method and the target optimization matrix to achieve matching calculation of the data.Finally,the user interaction module and the data display platform are completed and implemented,and the housing rental data recommendation system is realized by integrating each module.Test results on the system show that the system can meet the data recommendation for users.