Map Data Moderation via Expertise-Based Review Ranking
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Solution Overview
Problem
Conventional map data acquisition is costly and time-consuming, leading to outdated maps due to infrequent verification, causing user frustration with errors and changes not being reflected promptly.
Innovation Solution
A system and method allowing users to contribute and review map edits, with a server and database comprising modules for inference, spam prevention, and publishing, which analyze and validate edits, prioritize reviewer expertise, and rapidly update map data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If expert observers are used to acquire map data, then reliability of map data is improved, but cost and time consumption increase
Solution Approach 1:
The patent replaces expensive expert observers with inexpensive user-contributed edits that can be rapidly submitted and processed. Individual user edits are treated as disposable contributions that are quickly validated through automated inference and community review, eliminating the need for costly expert field work while maintaining data reliability through collective verification.
Solution Approach 2:
The system enables map data acquisition through self-service mechanisms where users automatically contribute edits to map data. The inference module analyzes these user submissions and the community review process validates them, creating a self-sustaining system that continuously updates map data without requiring external expert intervention for each correction.
2Reliability
If expert observers are used to acquire map data, then reliability of map data is improved, but cost increases
Solution Approach 1:
The patent replaces expensive expert observers with inexpensive user-contributed edits that can be rapidly submitted and processed. Individual user edits are treated as disposable contributions that are quickly validated through automated inference and community review, eliminating the need for costly expert field work while maintaining data reliability through collective verification.
Solution Approach 2:
The system creates a universal platform where any user can contribute map data edits, and any reviewer can validate them. This multi-functional system combines data collection, validation, and publication capabilities in a single community-driven platform, replacing the specialized function of expert observers with a universal user-contributed model that reduces costs while maintaining reliability.
3Quantity of substance
If map data is not verified frequently, then cost is reduced, but map data becomes outdated
Solution Approach 1:
The patent implements continuous verification of map data through an always-active system where user edits are continuously submitted, analyzed by the inference module, and reviewed by the community. This continuous cycle of contribution and validation ensures map data remains current without requiring periodic expensive expert verification campaigns, maintaining accuracy through uninterrupted community engagement.
Solution Approach 2:
The inference module performs preliminary analysis of user-edited map data before it reaches the review stage, automatically validating edits against existing map data and identifying obvious errors. This preliminary filtering action reduces the burden on reviewers and ensures that only plausible edits proceed to community review, maintaining data accuracy while reducing verification costs and time.
4Productivity
If user-contributed edits are accepted without review, then productivity is improved, but reliability deteriorates
Solution Approach 1:
The inference module performs preliminary analysis of user-edited map data before it reaches the review stage, automatically validating edits against existing map data and identifying obvious errors. This preliminary filtering action reduces the burden on reviewers and ensures that only plausible edits proceed to community review, maintaining data accuracy while reducing verification costs and time.
Solution Approach 2:
The system implements feedback mechanisms where reviewers provide validation or rejection of user edits, and this feedback is used to improve the inference module's analysis capabilities. The community review process generates feedback loops that continuously refine the system's ability to automatically validate edits, increasing productivity over time while maintaining reliability through learned patterns of accurate versus inaccurate submissions.
Data Source
AI summary
A geographic information system allows users to access a map database and to contribute map data to the database. Proposed edits to the map are queued for review by a reviewer users. Reviewing users can subscribe to review edits in regions and/or to types of map features. Reviewers can share their subscriptions with other reviewers. In the moderation queue, the proposed edits are ranked and those edits proposed by users who also review are optionally ranked higher and thus reviewed sooner than edits proposed by users who do not review or review less. The history of reviewers is analyzed to identify those with expertise in a particular region and/or type of map feature. One embodiment of the system includes a database containing geographic data, an inference module, a spam prevention module, a reviewing module and a publishing module.


