Transaction Annotation Integration for Cross-Platform Schema Tagging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional systems for annotating transactions across different third-party platforms consume excessive processing and storage resources due to the lack of standardized schemas, leading to inaccurate and resource-intensive metadata tagging.
Innovation Solution
A computing server creates transaction accounts for organizations, allowing clients to specify annotation requirements and selection criteria, distributes the annotation task to end users through direct links, and aggregates annotated data using a graphical user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a server automatically determines and stores annotations for transactions using third-party platform schemas, then transactions can be monitored and organized across multiple platforms, but processing and storage resources are consumed excessively
Solution Approach 1:
The patent applies self-service by enabling end users to manually annotate their own transactions through direct links sent to their devices. Instead of the server performing all annotation work, the system empowers users to self-annotate transactions by selecting from predefined schema options, thereby distributing the processing burden and reducing server resource consumption while maintaining comprehensive transaction monitoring capability
Solution Approach 2:
The annotation task is segmented into two parts: the server provides the infrastructure, schema definitions, and direct links, while end users perform the actual annotation work on their own devices. This segmentation divides the previously centralized processing load into distributed user actions, reducing server processing and storage resource requirements while preserving the ability to monitor and organize transactions across multiple third-party platforms
2Productivity
If a server infers metadata tags from scant transaction information, then annotations can be generated automatically, but annotation accuracy decreases
Solution Approach 1:
The system enables end users to self-annotate transactions with accurate metadata tags by presenting them with direct links containing predefined schema options. Users leverage their own knowledge and context to accurately categorize transactions, eliminating the inaccuracies inherent in server-based inference from limited data while maintaining efficient annotation generation through the automated direct link delivery mechanism
3Adaptability or versatility
If a server creates different data structures for each third-party platform schema, then platform-specific requirements are met, but storage complexity increases
Solution Approach 1:
The patent implements universality by using a standardized annotation data structure that works across all third-party platforms. Instead of creating separate data structures for each platform schema, the system defines a universal annotation format with fields like annotation_id, transaction_id, platform_name, schema_name, and annotation_values that can accommodate multiple platform requirements through configuration rather than structural differentiation, thereby reducing storage complexity while maintaining platform compatibility
Data Source
AI summary
A system for annotating transactions includes a computing server configured to retrieve annotation requirements for transaction accounts of an organization client, where the annotation requirements specify a data field of a third-party platform's schema that is used to organize transaction data. The organization client may further specify which transactions need to be annotated using selection criteria. The computing server processes transactions incurred using the transaction accounts and identifies unannotated transactions using the selection criteria. End users who are responsible for annotating the unannotated transactions are provided direct links to annotate the unannotated transactions. Upon receiving annotations from the responsible end users, the computing server can display annotated transaction data for an administrator of the organization client.