Semantic Vector API Schema Mapping
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Solution Overview
Problem
Integrating external APIs with internal APIs is cumbersome due to differences in naming conventions and organizational structures, requiring significant effort and being prone to errors.
Innovation Solution
Computing external semantic vectors for external API schema properties and internal API schema properties, allowing for the selection and mapping of candidate external schema properties to internal schema properties, thereby automating the integration process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual integration of external API with internal API is performed, then mapping accuracy can be ensured through human judgment, but integration time and effort increase significantly
Solution Approach 1:
The patent introduces semantic vectors as an intermediary representation between API schema properties. These vectors capture the semantic meaning of properties (such as 'user_name' representing a person's name) and enable automated comparison and matching between external and internal APIs, reducing manual intervention while maintaining accuracy
Solution Approach 2:
The patent transforms API schema properties into semantic vector representations, changing the parameter form from textual property names to numerical vector embeddings. This transformation enables automated computational comparison using cosine similarity or other distance metrics, significantly reducing manual mapping time while preserving semantic meaning for accurate matching
2Ease of manufacture
If automated mapping using semantic vectors is implemented, then integration effort is reduced, but complexity of the mapping system increases
Solution Approach 1:
The patent employs universal semantic vector representations that can be applied across different API schemas and domains. The same semantic vector framework handles diverse property types (user names, product names, organizational structures) uniformly, reducing the need for domain-specific customization and simplifying the overall system architecture
Solution Approach 2:
The patent creates simplified semantic vector copies of complex API schema properties. Instead of manually analyzing and mapping entire API structures, the system generates compact semantic representations (vectors) that capture essential meaning, enabling automated comparison without dealing with the full complexity of the original schemas
3Measurement precision
If comprehensive semantic vectors are computed using multiple properties, then mapping precision improves, but computational cost increases
Solution Approach 1:
The patent computes semantic vectors selectively based on the specific mapping task requirements. Rather than always computing exhaustive semantic representations for all properties, the system can compute vectors only when needed or use pre-computed vectors from existing semantic databases, balancing precision requirements with computational efficiency
Data Source
AI summary
Application programming interfaces (APIs) may have different API schemas that may have different organizations of schema properties and entities or use different names for schema properties and entities. Where two or more APIs with different schemas are being used, it may be desired to map schema properties and/or entities between them. Semantic representations of API schema properties and entities may be used to assist with the mapping of schema properties and entities. The semantic representations may be used to suggest possible mappings to a user or to automatically determine a mapping without the involvement of a user.