Travel Booking Search Normalization Engine
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Solution Overview
Problem
The complexity of airfare pricing dynamics, numerous airlines and routes, and varying user preferences lead to inefficiencies in travel booking searches, resulting in repeated queries and resource wastage due to discrepancies and overwhelming options, particularly for corporate travel.
Innovation Solution
A computing resource optimization engine that normalizes travel booking search results by parsing heterogeneous data from multiple travel actor servers, merging fare classes, and controlling a graphical interface to display relevant itineraries based on administrator-defined parameters, reducing redundant searches and optimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If travel booking search systems query multiple travel actor servers for comprehensive itinerary options, then the completeness and variety of travel options improve, but the complexity of handling heterogeneous data formats and the computational resources required increase
Solution Approach 1:
The patent introduces a normalization layer that acts as an intermediary between heterogeneous travel actor servers and the search system. This normalization layer standardizes data formats from different airlines and travel agencies into a common structure, eliminating the need to handle each provider's unique format individually while maintaining comprehensive travel options.
Solution Approach 2:
The patent implements data normalization that converts heterogeneous data formats from multiple travel actors into a homogeneous standardized format. This allows the system to process and compare itineraries from different sources uniformly, reducing complexity while preserving the completeness of travel options across multiple providers.
2Loss of information
If the system displays all available travel itineraries with detailed parameters, then the information completeness improves, but the user interface complexity and processing time increase
Solution Approach 1:
The patent segments travel itinerary parameters into hierarchical groups (e.g., flight details, pricing, amenities, restrictions). This segmentation allows the system to organize comprehensive information in a structured manner, enabling efficient processing and selective display based on user preferences without overwhelming the interface.
Solution Approach 2:
The patent implements dynamic parameter display where the system adapts the level of detail shown based on user interactions and preferences. Frequently important parameters are displayed prominently while less critical details can be accessed on demand, reducing initial processing time while maintaining information completeness.
3Measurement precision
If the system performs multiple refined searches to account for user preferences and corporate policies, then the accuracy of results improves, but the network and computing resources consumed increase
Solution Approach 1:
The patent applies preliminary filtering of travel itineraries based on corporate policies and user preferences before conducting detailed searches. By pre-establishing constraint parameters (e.g., acceptable layover durations, preferred airlines, budget limits), the system reduces the search space early, improving result accuracy while minimizing resource consumption on subsequent refined searches.
4Ease of operation
If the system normalizes heterogeneous fare classes from different travel actors, then the ease of comparison improves, but the complexity of mapping diverse fare attributes increases
Solution Approach 1:
The patent transforms diverse fare class attributes from different travel actors into standardized parameters through normalization. By mapping varying fare attributes (refundability, change policies, included amenities) to a common parameter framework, the system enables easy fare comparison while managing mapping complexity through systematic parameter transformation.
Data Source
AI summary
The present specification provides, amongst other things, a computing resource optimization engine that can normalize heterogenous travel itinerary data from different travel actor engines and generate a normalized itinerary on a display device.