Exemplar Electronic Document Generation via Semantic Context
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Solution Overview
Problem
The absence of contextual information limits insight into appropriate travel accommodations, making it a burdensome manual effort to identify suitable hotels, flights, and transportation, and non-conforming travel arrangements are resource-intensive to audit.
Innovation Solution
Generating exemplar electronic documents based on contextual information using a knowledge graph for semantic comparison and correlation, which includes processing user input to identify semantic differences and correlations, and pre-populating trip details for optimized travel itineraries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual identification of travel arrangements is used, then flexibility in selecting accommodations is maintained, but the process becomes burdensome and time-consuming
Solution Approach 1:
The system performs preliminary actions by pre-processing travel data, user profiles, and policy information into structured knowledge graphs before actual travel planning is needed. This includes pre-computing semantic relationships, organizing accommodation options by user preferences, and establishing policy constraints in advance, so that when a user needs travel arrangements, the system can quickly retrieve and assemble appropriate recommendations without performing heavy computation in real-time.
2Loss of information
If contextual information is not used, then the system remains simple, but insight into appropriate travel accommodations is limited
Solution Approach 1:
The patent introduces knowledge graphs as intermediary structures that bridge raw contextual information and travel recommendation outputs. These knowledge graphs serve as mediators by structuring unstructured travel data, user profiles, and policy information into organized semantic networks that can be efficiently queried. This intermediary layer enables sophisticated contextual analysis without requiring the entire system to be complex, as the knowledge graphs handle the complexity of information integration while presenting simplified interfaces for recommendation generation.
3Reliability
If comprehensive travel arrangements are manually audited for policy conformance, then compliance accuracy is improved, but resource burden increases
Solution Approach 1:
The system implements feedback mechanisms where policy constraints and compliance rules are continuously integrated into the travel recommendation process. As the system generates travel arrangements, it automatically checks recommendations against stored policy information and user profiles, providing real-time feedback on compliance status. This allows the system to maintain high reliability for policy conformance while improving productivity by eliminating the need for separate manual audit processes, as compliance verification is embedded in the recommendation generation itself.
Data Source
AI summary
Implementations are directed to providing an exemplar electronic document (EED) with actions including receiving input that is at least partially representative of a subject, receiving a plurality of stored subjects, each including data representative of a respective stored subject, and provided in a knowledge graph, processing the input based on semantic comparison between the input and each of the stored subjects to provide a set of semantic differences, each semantic difference representing the input and a respective stored subject, processing a profile in view of each of a plurality of other profiles to provide a set of semantic correlations, each semantic correlation representing the profile and a respective other profile, and providing the EED based on the sets of semantic differences and semantic correlations, the EED including at least a portion of the input, and respective portions of each of a plurality of stored subjects based on respective scores.