Taxonomy Graph Matching for Direct Translation Provider Selection
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Solution Overview
Problem
Existing translation services often rely on intermediaries, which can increase costs and reduce transparency, and there is a lack of efficient systems for matching service requesters with service providers based on specific skills and immutable quality scores.
Innovation Solution
A taxonomy-based directed graph is used to match service requesters with service providers, ranking them based on skill distance and immutable quality scores stored in a blockchain, allowing direct selection without intermediaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If intermediaries are used to provide translation services, then service coordination is facilitated, but costs increase and transparency decreases
Solution Approach 1:
The patent extracts the intermediary function from the service delivery system by implementing a direct matching mechanism between service requesters and providers. The taxonomy-based directed graph and blockchain technology enable requesters to independently identify and select suitable providers without intermediary involvement, thereby eliminating the cost losses associated with intermediary services while maintaining service coordination capabilities.
Solution Approach 2:
The system enables service requesters to perform self-service by autonomously identifying and selecting appropriate service providers through the taxonomy-based matching system. Requesters can directly query the directed graph, evaluate provider qualifications based on immutable quality scores stored on blockchain, and make selection decisions without intermediary assistance, thus reducing operational costs while maintaining coordination effectiveness.
2Ease of operation
If intermediaries are used to provide translation services, then service coordination is facilitated, but transparency decreases
Solution Approach 1:
The patent removes the intermediary layer that obscures information between requesters and providers. By implementing direct access to provider profiles and immutable quality scores on blockchain, the system extracts the information-filtering function from intermediaries, allowing requesters to transparently view provider qualifications, performance history, and pricing information without intermediary interference or information distortion.
Solution Approach 2:
The system implements transparent feedback mechanisms through blockchain-stored immutable quality scores and performance records. Provider performance data is openly accessible to requesters, creating a transparent feedback loop that eliminates information asymmetry. This allows requesters to make informed decisions based on verifiable historical performance data rather than intermediary-filtered information.
3Measurement precision
If taxonomy-based directed graph matching is implemented, then service provider selection accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the service matching problem into hierarchical layers using the taxonomy-based directed graph. The graph structure divides service domains into parent categories and child specialties, allowing the matching system to operate at different levels of granularity. This segmentation enables accurate matching by breaking down complex service selection into manageable hierarchical steps, reducing the computational complexity of evaluating all possible provider-service combinations simultaneously.
Solution Approach 2:
The system adds a hierarchical dimension to the service matching process through the directed graph structure. Instead of flat, single-dimension matching, the taxonomy introduces multiple hierarchical levels (parent categories, child specialties, specific services) that organize provider skills and service requirements. This dimensional organization improves matching accuracy by enabling multi-level filtering and comparison, while the hierarchical structure naturally reduces complexity through progressive specialization.
Data Source
AI summary
Systems, methods, devices, and non-transitory, computer-readable storage media are disclosed for matching a service requester with a service provider via a taxonomy based directed graph. The method includes: receiving a keyword associated with a service; accessing a directed graph including a root node and nodes connected by edges, each node having a title; identifying a second node of the directed graph for each of service providers, each second node having a title matching a skill of a respective service provider; determining a distance between the first node and each second node along the directed graph; and ranking the service providers based at least in part on the distance between the first node and each second node. Systems, methods, devices, and non-transitory, computer-readable storage media are further disclosed for determining and storing a quality score for the revised linguistic content.