Research And Implementation Of Location Service Information Integration And Search System

With the development of Internet,especially the development of Mobile Internet Technology in the past 10 years,location-based service information has become more and more important,such as rental service,housekeeping service,merchant service,hotel service and other service information.Basically,service information related to food,clothing,housing and transportation can be published on the Internet,and more and more information will be accompanied by location coordinates.How to collect,analyze,store and provide personalized search services based on users is a real problem that needs to be solved.This paper realizes the collection of location service information from the Internet and users,and analyzes,stores and indexes the collected data,and realizes personalized search for service information.Let users search for the required service information accurately,conveniently and personalizedly.The main work of this paper is as follows:1.Aiming at the anti-crawling strategy of target sites in the process of collecting location service information from the Internet,in order to improve the collection efficiency of demand data,a crawler model based on client-server model was designed,developed and implemented.The server is responsible for dynamically controlling the production,scheduling,and collection of the task URLs.The client program periodically requests the task URL and collects the required data.The client designs a strategy to dynamically change the collection settings to achieve optimal collection efficiency.The server dynamically generates an appropriate number of task URLs according to the efficiency of the client's consumption tasks.The collection,coordination,and collection of the results of the task is accomplished by setting up monitoring,a series of scheduled tasks,and a task table.The task table status field precisely controls the status of the collection task to ensure the timeliness and integrity of the data collection.Through the collection test and comparison with other crawlers,the practicality of the design task production and scheduling strategy and the dynamic adjustment strategy of the client acquisition setting are verified.The model enables more and more nodes to serve data collection and achieves an expected collection efficiency.2.In order to enable users who can provide personalized services to conveniently publish various service information with location coordinates,a background program and a mobile APP for collecting location service information modules from users are designed and developed.The background program is built on the Java Web layered architecture using the SSM framework,and the interface program related to the data collection service is designed.The mobile terminal applies the Baidu map SDK design component and interface based on the Android Studio development environment,and realizes collecting different types of location service information from the users providing the service.The location information acquisition module includes map positioning,selection point acquisition coordinates,and coordinate and address information mutual conversion functions.The new store and service information module is designed with the service category prompt function.The category information is maintained by the category code table.At the same time,the function of photographing and album selection,and the interaction between the image data of the mobile terminal and the background program is realized.3.In order to allow users to easily input personalized query information through the search box,and accurately find the intent query results,this paper designs and implements a personalized search engine based on location service information.First,the Elasticsearch distributed cluster was built according to the production environment configuration requirements.After that,the domain lexicon and vocabulary level weight table are constructed according to certain rules for the integrated location service information.The domain lexicon is used to improve the accuracy of indexing and querying data.The vocabulary rating level table is used to assign a corresponding weight to keywords appearing in the table when constructing the query statement to increase the relevance score.The mobile terminal is designed with a query keyword input prompt rule to allow the user to input the intent query information in one time and conveniently.The background program extracts the query information according to certain rules and constructs a personalized index library query statement.Finally,through the example verification,the personalized search engine enables the user to input query information in a one-time and convenient manner and respond to the query results required by the user quickly and accurately.