Image Geocoding via User Search Queries and Textual Documents
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems face challenges in accurately and efficiently geocoding images without associated location information, as they require significant computing resources and often misclassify images based on textual content or lack explicit location-specific visual content.
Innovation Solution
A method that determines a selection value for each search string associated with an image based on user selections, generates a textual document, identifies geographic entities using a textual processor, and selects a primary geographic entity to assign a geocode, with auxiliary entities and quality values calculated for precision and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If computerized analysis of image content is used to match images to locations, then location identification can be achieved, but significant computing resources are required making it impractical for large-scale application
Solution Approach 1:
The patent introduces search queries and textual documents as intermediary elements between the image and location matching process. Instead of directly analyzing image content to determine location, the system uses user-provided search queries and associated textual documents as mediators that contain location information, thereby avoiding computationally intensive image analysis while still achieving accurate location identification
Solution Approach 2:
The patent replaces the mechanical/computational image analysis system with a text-based information retrieval system. By substituting the complex computerized image content analysis with simpler text processing of search queries and documents, the system achieves location identification with significantly reduced computing resources
2Productivity
If geocoding is performed based solely on textual content in web documents, then processing is simpler, but a significant number of images are miscategorized or not categorized at all
Solution Approach 1:
The patent incorporates user search queries and selections as feedback mechanisms to improve geocoding accuracy. By analyzing which search queries lead to which images and how users interact with search results, the system refines its geocoding decisions, ensuring that textual content analysis produces more accurate and reliable location assignments
Solution Approach 2:
The patent performs preliminary analysis of search query patterns and user selections before finalizing geocoding decisions. By pre-processing and analyzing the relationship between search queries, textual documents, and user interactions, the system prepares accurate location assignments in advance, improving both speed and reliability of the geocoding process
Data Source
AI summary
Systems and methods for determining a geocode for an image based on user-provided search queries and corresponding user selections are provided. One example method includes determining a selection value for each of a plurality of search strings associated with an image based at least in part on user selection data. The method includes generating a textual document for the image based at least in part on the selection values. The textual document includes one or more of the plurality of search strings. The method includes identifying a plurality of geographic entities by analyzing the textual document using a textual processor. The method includes selecting one of the plurality of geographic entities as a primary geographic entity and associating, by the one or more computing devices, a geocode associated with the primary geographic entity with the image.