Design And Implementation Of A Real Estate Search System Based On Elasticsearch

At present,the social economy is developing rapidly,and the incoming level are getting higher and higher,but the housing price is still high for most people.People will choose to rent a house when they just enter the society,and in the face of a large amount of housing information,people find it difficult to find the housing source they need.Traditional house searching systems provide search services without considering users' interests and preferences.when different users querying the same keywords,it often return the same results and can not meet the personalized needs of users.The system designs and implements a housing information service system with personalized search engine function on the basis of in-depth study of user model and open source search engine Elasticsearch technology.Based on simple operation,friendly interface and practical function and other aspects,the whole system provides convenient and comprehensive housing rental and sales information which helps customers can quickly and accurately find their own ideal housing for customers and offers a simple and effective housing information releasing,managing,renting platform for the administrator.According to the idea of software engineering and combined with the actual needs of users,the housing search system is divided into the front-end user and the background administrator sections.The front-end user system is divided into user login,housing search,map search,reservation viewing and personal center five modules.The background administrator system is divided into two modules: housing management and reservation management.The system is designed and implemented on the basis of two sections.The main innovation and research contents are as follows: achieving in-station search engine based on Elasticsearch,including Elasticsearch housing source statistics function based on aggregation function and automatic hint function of Suggest.According to the characteristics of the housing source information ontology,the user model is implemented by using vector space representation to provide model support for personalized search.realizing house finding with Elasticsearch and Baidu map,including basic map display and application of baidu location service(LBS).The results of the system function tests and performance tests indicate the desired needs.After introducing personalized search,it can provide more effective and intelligent search results for different users.It reduces users' work and has certain practical application value.