Location Search Augmentation via Secondary Datastore Segmentation
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Solution Overview
Problem
Current location-based services are limited in their ability to incorporate external, proprietary, or custom data fields into search results, which can lead to incomplete information and reduced accuracy, as they primarily rely on pre-indexed data within their primary databases, failing to leverage external data sources effectively.
Innovation Solution
A system and method that augment search results by integrating external data fields not contained in the primary datastore, using a secondary datastore to enrich candidates with additional information, allowing for the inclusion of proprietary and custom data while maintaining search efficiency through entity matching and augmentation processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If location-based services rely solely on pre-indexed data within primary databases, then search speed and system simplicity are maintained, but information completeness and accuracy deteriorate due to inability to incorporate external proprietary or custom data fields
Solution Approach 1:
The system divides data storage into separate primary and secondary datastores, where the primary datastore contains pre-indexed location data for fast searching, while the secondary datastore stores external proprietary or custom data fields. This segmentation allows the system to maintain search speed using the primary datastore while enriching results by selectively augmenting with relevant data from the secondary datastore, thus improving information completeness without significantly increasing overall system complexity.
Solution Approach 2:
The system performs preliminary indexing of location-based data in the primary datastore, organizing it in advance for efficient querying. Additionally, external data fields from the secondary datastore are pre-processed and structured to enable rapid augmentation during search operations. This preliminary preparation ensures that when a search is executed, the system can quickly retrieve base results and efficiently augment them with external data, improving information completeness without sacrificing search speed.
2Loss of information
If external data sources are integrated into search results, then data diversity and relevance are improved, but search processing time and computational resources increase
Solution Approach 1:
The system applies partial augmentation by selectively adding only those external data fields from the secondary datastore that are relevant to the specific search query and location candidates. Rather than retrieving and processing all external data for every search, the system performs targeted augmentation based on query requirements, thus improving data diversity and relevance while minimizing the additional processing time and computational resources required.
3Measurement precision
If multiple datastores are used to augment search results, then data accuracy and relevance are enhanced, but system complexity and data management difficulty increase
Solution Approach 1:
The system introduces an intermediary augmentation module that acts as a mediator between the primary and secondary datastores. This module receives search results from the primary datastore, identifies candidates for augmentation, retrieves relevant external data fields from the secondary datastore, and integrates them into the final results. The intermediary handles data matching, validation, and integration logic, thereby enhancing data accuracy through multi-source verification while shielding the rest of the system from the complexity of managing multiple datastores.
Data Source
AI summary
System and methods for augmenting search results with external/user-provided data fields not contained in a primary datastore. A method includes receiving, by a processor, a location-based query; searching, by the processor, a primary datastore for one or more candidates for the location-based query; identifying, by the processor, one or more data fields for the one or more candidates contained in a secondary datastore, the one or more data fields not contained in the primary datastore; augmenting, by the processor, the one or more candidates with the one or more data fields; and providing, by the processor, the augmented one or more candidates.