Entity Extraction Model for Automated Shipping Booking Modifications
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Solution Overview
Problem
The existing methods for processing booking modifications in shipping systems are inefficient, prone to human subjectivity, and result in delays due to complex validation rules, impacting customer satisfaction and resource management.
Innovation Solution
An electronic device and method that utilize an entity extraction model to automate booking data modifications by obtaining a text dataset, determining a modification set with confidence parameters, and outputting a modification output for processing booking changes, thereby reducing manual intervention and improving accuracy and consistency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing methods are used for booking modifications, then human judgment and flexibility can be applied, but processing time increases and consistency decreases
Solution Approach 1:
The patent replaces manual mechanical processing with an automated entity extraction model that uses natural language processing to identify and extract booking modification details from text data. This substitution eliminates human subjectivity and significantly reduces processing time while maintaining high accuracy through consistent application of extraction rules.
Solution Approach 2:
The system enables self-service processing by automatically extracting modification entities from input text, validating them against predefined rules, and generating modification outputs without requiring human intervention for routine bookings. This self-service mechanism handles high volumes of modifications efficiently while reserving human judgment for complex edge cases.
2Productivity
If automated entity extraction is implemented, then processing speed and consistency improve, but system complexity increases
Solution Approach 1:
The patent segments the booking modification process into distinct components: text input reception, entity extraction, validation against business rules, and modification output generation. This segmentation allows each component to be independently optimized and managed, reducing overall system complexity while maintaining high productivity through parallel processing capabilities.
Solution Approach 2:
The entity extraction model is designed as a universal system that can handle multiple types of booking modifications across different shipping scenarios through a single standardized interface. The model extracts various entity types (dates, locations, shipment details) using the same underlying technology, eliminating the need for separate processing systems for each modification type.
3Reliability
If human subjectivity is reduced in processing, then consistency and reliability improve, but automation requirements increase system complexity
Solution Approach 1:
The system incorporates feedback mechanisms where extraction results are validated against predefined business rules and historical data patterns. When extraction confidence is low or rules are violated, the system flags items for human review, creating a feedback loop that continuously improves extraction accuracy while maintaining consistency through automated validation of successful extractions.
Data Source
AI summary
Disclosed is a method, performed by an electronic device, for modifying booking data for a shipping system. The method comprises obtaining a text data set. The method comprises determining, based on the text data set and an entity extraction model, a modification set comprising an entity parameter and a first modification parameter. The first modification parameter is associated with a first confidence parameter. The method comprises outputting, based on the modification set, a modification output for modifying the booking.