Event Template Generation Using Transaction Data Normalization
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Solution Overview
Problem
Existing software platforms lack the ability to optimize transactions between computing devices by identifying capable devices and generating optimal software event templates based on prior transaction data, due to inconsistent identification of devices and events across different systems.
Innovation Solution
A server computer tracks transactions between devices, normalizes identifiers, and generates event templates by analyzing past transaction data to recommend suitable devices and items for specific event types, facilitating transactions and optimizing event creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a server computer stores data relating to past transactions and past events, then the system has access to historical transaction information, but the data is not uniform in the way computing devices are identified, events are identified, or items of transactions are identified
Solution Approach 1:
The patent introduces an intermediary normalization layer that mediates between diverse incoming transaction data and the standardized storage format. This normalization layer translates various identifier formats (device identifiers, event identifiers, item identifiers) into a unified internal representation, allowing the system to store heterogeneous data uniformly without requiring changes to the underlying data diversity.
Solution Approach 2:
The system applies parameter changes by transforming identifier parameters from their original diverse formats into standardized formats during the normalization process. This allows the same type of information (device identification, event identification, item identification) to be represented consistently across all stored transactions while preserving the ability to recognize and process different identifier types.
2Loss of information
If the system normalizes identifiers across transactions, then data uniformity is improved, but processing time and computational resources increase
Solution Approach 1:
The patent implements preliminary action by performing identifier normalization at the point of data ingestion, before the data is stored or processed further. This upfront normalization ensures that all subsequent operations work with already-standardized data, eliminating the need for repeated normalization operations and reducing overall processing time.
Solution Approach 2:
The system creates normalized copies of identifiers during the initial processing stage. These normalized identifier copies are stored alongside or in place of the original identifiers, allowing rapid retrieval and comparison operations without requiring real-time normalization of the original diverse identifier formats.
3Productivity
If the system generates event templates based on prior transaction data, then transaction optimization is improved, but the complexity of the system architecture increases
Solution Approach 1:
The patent applies preliminary action by pre-generating event templates from historical transaction data during periods when the system is not processing live transactions. These templates encapsulate optimized transaction patterns and can be rapidly applied to new transaction requests, improving efficiency without adding complexity to the real-time transaction processing path.
Solution Approach 2:
The system creates simplified copies of successful transaction patterns in the form of event templates. These templates represent distilled versions of complex historical transaction sequences, allowing the system to replicate proven successful transactions without re-analyzing the full complexity of the original transaction data each time.
Data Source
AI summary
Systems and methods for generating event templates for requested event types are described herein. In an embodiment, a server computer receives transactional data describing transactions between a plurality of computing devices. The server computer uses the transactional data to identify a plurality of instances of a particular event type by determining, for each instance, that a plurality of transactions associated with a particular computing device relate to an event of the particular event type. The server computer uses the transactional data related to the plurality of instances of the particular event type to determine a plurality of items for the particular event type. When the server computer receives a request from a client computing device to generate an event, the server computer generates and displays an event template which identifies the plurality of items.