Social Network Mining for Real-Time Map Data Generation
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Solution Overview
Problem
Service providers and device manufacturers face challenges in generating accurate and substantially real-time geospatial data in a cost-effective manner for mapping and location-based services, as traditional methods are costly and crowd sourcing requires significant intentional effort from a limited number of individuals.
Innovation Solution
A system that monitors communications within social networks to process and extract map-related information, using linguistic analysis and pattern recognition to determine accurate data, which is then made available to mapping and location-based services, leveraging the volume of user-generated content without relying on specific communities or individuals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional geospatial data collection approaches are used, then data accuracy is maintained, but cost increases significantly
Solution Approach 1:
The patent uses social network communications as an intermediary source to collect geospatial data. Instead of directly deploying expensive traditional collection methods, the system intermediates through existing social network platforms where users naturally share location and map-related information, thereby reducing costs while maintaining data accuracy through verification processes
Solution Approach 2:
The system leverages users' own social network communications and posts to provide geospatial data without requiring dedicated data collection efforts from users. Users inadvertently contribute data through their normal social media activity, eliminating the need for separate crowd-sourcing campaigns or paid data collection services
2Loss of energy
If crowd sourcing methods are used, then cost is reduced, but data accuracy and reliability deteriorate due to lack of intentional effort from users
Solution Approach 1:
The system continuously monitors and processes social network communications in real-time, maintaining a steady stream of data collection without interruption. This continuous monitoring ensures that data is constantly being gathered and updated, improving reliability through consistent data flow rather than intermittent crowd-sourcing campaigns
Solution Approach 2:
The system processes and analyzes social network communications to verify data quality, using feedback loops to identify and filter inaccurate information. By analyzing patterns across multiple user communications and cross-referencing data points, the system can validate accuracy without requiring intentional user effort or dedicated verification teams
3Reliability
If traditional geospatial data collection is used, then data quality is maintained, but real-time responsiveness is reduced
Solution Approach 1:
The system pre-processes and monitors social network communications as they occur, preparing data for immediate use before traditional collection cycles would complete. By continuously scanning and preliminarily processing social media posts and communications, the system has data ready for rapid deployment when needed, achieving both quality and real-time responsiveness
Data Source
AI summary
An approach is provided for generating accurate and substantially real-time map and location-based data in a cost-effective manner. Specifically, one or more communications within one or more social networks are monitored, processed, and mined to determine map-related information (e.g., maps, traffic, points of interest). The map-related information is then subjected to one or more threshold criteria (e.g., a correctness probability, a level of confidence, a degree of trust, an author's influence, a rating, or a combination thereof) to better ensure its accuracy before being made available to mapping and/or location-based services that can use the map-related information to develop better quality maps and/or location-based mobile applications (e.g., improved routing guidance, location recommendations, etc.). By providing mapping and location-based services with accurate and real-time map and location-based data, the services can fulfill user's increasing expectation and demand for up-to-the-minute information.