Canonical Fact Ranking for Temporal Event Relationship Search
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Solution Overview
Problem
Existing information extraction systems struggle to effectively rank and utilize canonical fact entries across wide area networks, limiting user ability to search, analyze, and trigger events based on temporal relationships.
Innovation Solution
A wide area network fact information service system that includes canonical fact entry storage, fact descriptor entry storage, and a ranker for ranking these entries based on various measures such as source credibility, entity importance, and temporal proximity, enabling iterative recalculations and parallel processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple data sources are aggregated to improve information completeness, then the quantity and variety of facts increase, but the complexity of ranking and processing these facts increases
Solution Approach 1:
The patent segments the ranking process into multiple independent components: source credibility ranking, entity importance ranking, temporal proximity calculation, and fact similarity measurement. Each component processes specific aspects of fact evaluation separately, then combines results to produce overall fact rankings. This segmentation allows the system to handle large quantities of facts from multiple sources without overwhelming complexity.
Solution Approach 2:
The patent introduces multiple ranking dimensions beyond simple fact matching: source credibility dimension, entity importance dimension, temporal proximity dimension, and fact similarity dimension. By evaluating facts across these multiple dimensions simultaneously, the system can process and rank large volumes of facts from diverse sources while maintaining organized, multi-criteria evaluation rather than single-metric processing.
2Reliability
If continuous ranking recalculations are performed to maintain up-to-date information, then the currency and accuracy of rankings improve, but the computational resources and time required increase
Solution Approach 1:
The patent implements periodic recalibration of source credibility rankings and entity importance rankings at scheduled intervals rather than continuously. Between recalibration cycles, the system uses the established rankings to efficiently process new facts. This periodic action maintains reliable, up-to-date rankings while avoiding the excessive computational resource consumption of continuous recalculations.
Solution Approach 2:
The patent performs preliminary ranking of data sources by credibility and preliminary ranking of entities by importance before actual fact processing occurs. These preliminary rankings are established in advance and reused for multiple fact evaluations, reducing the need for repeated full-scale calculations. This preliminary action ensures accurate, reliable rankings while minimizing ongoing computational resource requirements.
3Measurement precision
If comprehensive fact descriptor entries are stored for each canonical fact, then the precision of fact matching and retrieval improves, but the storage requirements and data processing complexity increase
Solution Approach 1:
The patent extracts and stores only the most relevant descriptor entries for each canonical fact, rather than storing all possible descriptors. The system identifies and retains key descriptors that are most useful for matching and retrieval operations, discarding redundant or less important descriptors. This extraction approach maintains high precision in fact matching while reducing storage requirements and data processing complexity.
Solution Approach 2:
The patent applies different levels of descriptor detail to different canonical facts based on their specific characteristics and importance. High-priority facts receive more comprehensive descriptor entries, while less critical facts use simplified descriptors. This local quality approach ensures high precision matching for important facts while reducing overall storage requirements by using lighter descriptors for less critical information.
Data Source
AI summary
In one general aspect, a wide area network fact information service method is disclosed. This method includes storing a plurality of canonical fact entries, storing one or more fact descriptor entries for each of the canonical fact entries, and ranking the canonical fact entries relative to each other based on the descriptor entries.