A Spatial Relationship Based Spatial Scene Data Retrieval Method

Abstract

The present invention discloses a space scenario data search method based on spatial relationship. The data search method comprises: step I, using a freehand search scenario as search input; step II, extracting a modified 9-intersection model semantic network from a database scenario and the search scenario; step III, extracting a basic directional relationship semantic network; step IV, creating an associated diagram of the 9-intersection model semantic network to obtain a preprocessing result set; step V, creating an associated diagram of the basic directional relationship semantic network with respect to the preprocessing result set to obtain a search result set; step VI, calculating a similarity score of search results in the search result set; step VII, if the current search result set is null or the number of search results in the search result set is smaller than a threshold, relaxing constraints of the spatial relationship, extending the search result set, and returning to the step IV, and otherwise, proceeding to the next step; step VIII, displaying the search results on an output device according to the similarity scores. The data search method provided by the invention has the advantages of improving search efficiency and enhancing user experience.

Description

technical field [0001] The invention belongs to the field of spatial retrieval, and in particular relates to a spatial relationship-based spatial scene data retrieval method that can improve retrieval efficiency. Background technique [0002] With the gradual realization of "Digital China", the application of spatial information is becoming more and more extensive. Digital vector maps have many advantages such as high precision, high-quality zoom support, accurate positioning, convenient operation, and convenient update. They have become necessary guarantee resources for geographic information systems, intelligent transportation systems, digital cities, and digital national defense construction. It overcomes the shortcomings of paper maps such as slow query speed, inconvenient storage, and low drawing accuracy, and is the cornerstone of the entire system. However, the retrieval of vector maps is still at the stage of mechanized retrieval based on database query language, an...

AI Technical Summary

Problems solved by technology

Digital vector maps have many advantages such as high precision, high-quality zoom support, accurate positioning, convenient operation, and convenient update. They have become necessary guarantee resources for geographic information systems, intelligent transportation systems, digital cities, and digital national defense construction. It overcomes the shortcomings of paper maps such as slow query speed, inconvenient storage, and low drawing accuracy, and is the cornerstone of the entire system

However, the retrieval of vector maps is still at the stage of mechanized retrieval based on database query language, which fails to fully utilize the spatial characteristics of vector data.

This traditional retrieval method is not only rigid, but also very inconvenient and error-prone for users

The main reason for these problems is that spatial retrieval has the characteristics of fuzzy, imprecise, difficult to understand and irregular input, which restrict the retrieval efficiency and hit rate of traditional spatial retrieval languages.

Images