Information Retrieval Scheduling Based on Issuance Cadence
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Solution Overview
Problem
Scheduling the collection of financial documents from third-party sources is challenging as it can lead to either wasting computational resources by retrieving documents too frequently when they are not available or keeping the accounting system outdated by retrieving them too infrequently.
Innovation Solution
A method and system that determine a predicted time for information retrieval based on historical data, using a scheduling application to optimize fetching runs by analyzing the cadence and issuance patterns of documents from third-party sources, adjusting for confidence scores and potential disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If information retrieval is performed too frequently, then the accounting system remains up-to-date, but computational resources are wasted
Solution Approach 1:
The patent implements dynamic scheduling of information retrieval by analyzing historical issuance patterns and predicting future availability times. Instead of using fixed frequent intervals, the system adapts retrieval schedules based on learned patterns from third-party document issuance behavior, optimizing the balance between data currency and resource consumption
Solution Approach 2:
The system incorporates feedback mechanisms by continuously monitoring retrieval success and updating predictions of document availability. The scheduling application learns from historical data about when documents are typically issued and adjusts future retrieval attempts accordingly, improving efficiency while maintaining system currency
2Loss of energy
If information retrieval is performed too late, then computational resources are conserved, but the accounting system becomes outdated
Solution Approach 1:
The system performs preliminary analysis of historical issuance patterns to predict future document availability before actual retrieval is needed. By understanding typical issuance cadences in advance, the system can schedule retrieval operations optimally, conserving resources while ensuring timely data updates
3Ease of operation
If fixed interval retrieval is used, then scheduling is simple, but retrieval efficiency is reduced due to unnecessary attempts
Solution Approach 1:
The system implements periodic retrieval actions based on predicted issuance patterns rather than fixed calendar intervals. By determining typical cadences from historical data (e.g., documents issued every 30 days), the system creates adaptive periodic schedules that are both simple to execute and highly efficient at avoiding unnecessary retrieval attempts
Data Source
AI summary
Described embodiments relate to methods, systems and computer program product for scheduling retrieval of candidate information from a first entity system at the predicted time. The method comprises determining a dataset associated with historical information issued by a first entity, wherein the dataset comprises a plurality of entries, each entry comprising an information date; determining a period of successful retrieval of information issued by the first entity, or a period of issuance of information by the first entity, based on the information dates of the plurality of entries in the dataset; determining a predicted time of issuance of future information by the first entity based on the determined period; and scheduling retrieval of candidate information from a first entity system at the predicted time.