Information Retrieval Scheduling by Predicted Document Availability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Scheduling the collection of financial documents from third-party sources is challenging as it can result in either wasting computational resources by retrieving documents that are not yet available or keeping accounting systems out-of-date by retrieving too late.
Innovation Solution
A method and system that determine a predicted time of information availability based on historical records of successful and unsuccessful fetching runs, using a scheduling application to schedule information retrieval accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If information retrieval is performed frequently to keep accounting systems up-to-date, then data freshness is improved, but computational resources are wasted when documents are not yet available
Solution Approach 1:
The system performs preliminary actions by analyzing historical issuance patterns and predicting future document availability dates before actually retrieving documents. This allows the system to schedule retrieval operations optimally - not too early (avoiding wasted resources) and not too late (maintaining data freshness). The prediction mechanism proactively determines the best retrieval timing based on learned patterns from historical data.
2Loss of energy
If information retrieval is performed less frequently to save computational resources, then resource efficiency is improved, but accounting systems become out-of-date
Solution Approach 1:
The system dynamically adjusts retrieval frequency based on learned patterns from historical data rather than using a static schedule. By analyzing issuance cadences and timing patterns, the system adapts retrieval operations to match actual document availability, optimizing the balance between resource efficiency and data currency. This dynamic approach allows the system to retrieve documents less frequently overall while still maintaining up-to-date data when documents are actually available.
3Device complexity
If fixed scheduling intervals are used for information retrieval, then system simplicity is maintained, but retrieval timing precision deteriorates
Solution Approach 1:
The system changes key parameters of the scheduling approach by moving from fixed time intervals to variable intervals based on predicted document issuance patterns. Instead of retrieving documents at regular intervals, the system adjusts retrieval timing parameters based on historical analysis of when documents are actually issued by third-party sources, significantly improving retrieval timing precision while maintaining reasonable system complexity through automated pattern recognition.
Data Source
Figure 1
Figure 2
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.