Research On Spatial Keyword Personalized Query And Results Visualization Approach

With the comprehensive popularization of mobile Internet,social networks,and global satellite positioning and navigation systems,the scale of applications of spatial data carrying geographic location information has grown rapidly,and location-based services(LBS)are playing an increasingly important role in people's lives.An increasingly important role.At the same time,spatial data comes from mobile Internet,user social networks,etc.,spatial data has the characteristics of massive,multi-dimensional,etc.,but with the gradual increase in user demand,ordinary spatial keyword query methods can no longer provide users with satisfactory results.Query results;at the same time,due to the massive characteristics of spatial data,the large amount of spatial data carrying geographic location information and social attributes generated in social network services poses greater challenges to the research of efficient query algorithms.With the gradual increase of location-based service systems(such as Meituan,Tongcheng Travel,Qunar,etc),it is becoming current to provide users with search results of geographical proximity and text content matching based on the user's geographic location and query keywords.Urgent need.Therefore,the research of spatial keyword query has become a major research hotspot in the current database query research field.The traditional spatial keyword query is centered on the geographic location of the user.Starting from the geographic location of the current user,the text matching query of adjacent spatial objects is performed based on the text keyword information provided by the user.The existing spatial keyword query methods mainly include Top-k range query and Top-k k nearest neighbor query.The two types of query methods mainly perform comprehensive scoring based on the text similarity and location similarity between the spatial object and the spatial keyword,and then use The text-space index technology improves the comprehensive query speed and query efficiency.In response to this problem,this paper proposes a scoring algorithm that can simultaneously calculate a set of spatial objects in a group of adjacent spatial objects on the basis of the existing spatial indexing algorithm;at the same time,the final query result of the keyword queried by the user is combined with The geospatial data visualization method presents the final results of the user's query in the form of map scatter points,and uses the visual open source development framework(Echarts)launched by Baidu to visualize the query results,so that users can finally get intuitive query results.The experiment compares the number of query keywords,the number of query results,and different experimental data sets.The query algorithm based on inverted files,the spatial index algorithm,and the better spatial index algorithm are compared,and the final experimental results are obtained.,The results show that the better spatial index algorithm is significantly better than the query algorithm and spatial index algorithm based on inverted files in performance.Query result visualization experiment simulates the user's input of query keywords in the process of personalized query of spatial keywords.According to the query keywords,the data set in South America is searched for spatial objects that meet the user's query conditions,and finally the visual query results required by the user are passed through the map.Presented in a scattered way.