Spatial Key Embedding for High Precision Local Search
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Solution Overview
Problem
Current search engines are inefficient for local searches due to the high cost and complexity of integrating spatial indexing and geocoding, which is error-prone and not effectively suited for non-standard address formats on the web.
Innovation Solution
Embedding spatial keys into map images allows search engines to index geographic locations directly, enabling precise local searches without the need for geocoding, using existing distribution channels and image encoding techniques like steganography.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search engine technology is used for local search, then search coverage is comprehensive, but search precision and accuracy deteriorate due to inability to perform spatial queries
Solution Approach 1:
The patent applies preliminary action by embedding spatial keys into map images during the image generation process, before the images are used in search operations. This pre-embedding of spatial information eliminates the need for complex post-processing spatial indexing, allowing search engines to perform local searches by simply matching query spatial keys against embedded keys in retrieved images
Solution Approach 2:
The patent uses copying by embedding spatial key information into map images that are already distributed through existing channels. Rather than creating a separate spatial index database, the spatial information is copied into the image format itself, allowing standard search engines to query spatial data without specialized spatial indexing infrastructure
2Adaptability or versatility
If geocoding is performed to enable local search, then spatial search capability is achieved, but processing speed deteriorates due to error-prone and slow geocoding processes
Solution Approach 1:
The patent inverts the traditional geocoding approach by not converting addresses to coordinates, but instead embedding spatial keys directly into map images at their source. This reversal eliminates the geocoding step entirely, as spatial information is captured and stored in the image format itself, enabling fast spatial queries without address parsing or coordinate conversion
Solution Approach 2:
The patent extracts the geocoding function entirely from the search process. By embedding spatial keys directly into map images during generation, the patent removes the need for separate geocoding operations, allowing search engines to perform spatial queries directly on embedded keys without address scraping, validation, or coordinate transformation
3Measurement precision
If commercial Yellow Pages databases are used for spatial search, then search accuracy is improved, but data coverage deteriorates due to limited scope of Yellow Pages data
Solution Approach 1:
The patent applies universality by making map images with embedded spatial keys serve multiple functions: they provide both visual mapping information and spatial search data. This multi-functionality allows standard search engines to perform spatial queries on any web page containing such images, dramatically expanding data coverage beyond specialized databases while maintaining spatial search accuracy
Solution Approach 2:
The patent enables self-service by allowing map images to carry their own spatial indexing information through embedded keys. Each map image becomes self-contained with spatial metadata, eliminating the need for centralized spatial databases or manual data entry, and automatically enabling spatial search capability across the entire web
Data Source
AI summary
High-precision local search is performed on the Internet. A map image-rendering software provider embeds spatial keys into maps, which are then provided to producers of Internet content such as map providers. For example, a homeowner may post a message on a web bulletin board advertising his house for sale, and including a map showing the location of the house. When a search engine's web crawler encounters a page having a spatial key embedded in an image, the spatial key is indexed with the other content on the page. Because the spatial key identifies a small geographic area, indexing the content with the spatial key allows search queries to be limited by area and still provide useful results. Thus, a user of a search engine searching for “house for sale” in a specific area will be directed to web pages that meet the geographic and content search terms.