Multi-Attribute Travel Booking Platform for Complex Itineraries
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Solution Overview
Problem
Existing travel booking platforms are unable to efficiently handle complex multi-passenger and multiattribute travel reservations, particularly for geographically distributed passengers with varied preferences and constraints, leading to a cumbersome consumer experience.
Innovation Solution
A system comprising a database, scheduler, and parser that processes user preferences to generate and rank feasible travel itineraries based on weighted attributes, providing a visual representation of multiattributed travel options that align with consumer preferences, including flight, hotel, and rental car information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing travel booking platforms are used to handle complex multi-passenger and multiattribute travel reservations, then the system can process basic travel bookings, but the consumer experience becomes cumbersome and the system cannot efficiently handle complex itineraries involving multiple geographically-distributed travelers
Solution Approach 1:
The patent segments the complex travel booking problem into distinct components: individual traveler profiles with unique preferences and constraints, multiple itinerary options, and attribute-based filtering. Each traveler can have separate preferences (e.g., departure times, destinations, budget constraints) that are independently processed and then integrated into coordinated group itineraries.
Solution Approach 2:
The system changes parameters by introducing weighted attribute scoring mechanisms that evaluate itineraries based on multiple dimensions (cost, convenience, traveler preferences). It transforms the booking process from simple search to optimized selection by adjusting and weighting multiple parameters simultaneously to resolve conflicts between different travelers' requirements.
2Loss of information
If the system provides comprehensive travel options with multiple attributes and preferences, then the consumer can make informed decisions, but the information abundance complicates the consumer choice problem
Solution Approach 1:
The patent introduces an intermediary processing layer that acts between the vast travel information database and the consumer. This intermediary automatically filters, organizes, and evaluates travel options based on predefined traveler profiles and preferences, presenting processed results rather than raw data. The system mediates between information abundance and decision-making by transforming unstructured options into ranked, profile-matched recommendations.
3Adaptability or versatility
If the system reconciles preferences of multiple passengers using integrated itineraries, then the group travel coordination is improved, but the computation-intensive routing and scheduling task becomes considerably more complex
Solution Approach 1:
The patent applies preliminary action by pre-processing and storing traveler preferences, constraints, and profile information before the actual itinerary generation. Traveler profiles including budget constraints, preferred departure times, and destination preferences are established in advance, allowing the system to quickly evaluate multiple routing options against pre-defined criteria rather than processing all constraints during real-time computation.
Data Source
AI summary
Systems and methods for facilitating multi-passenger and multiattribute travel reservations are presented. The system has a database, a scheduler, a parser, and a processor. The database stores a travel lexicon having attribute names and a travel taxonomy having look-up tables. The scheduler instantiates travel attributes in terms of the travel lexicon to generate instantiated user preferences, indexes the instantiated user preferences, and searches for feasible travel itineraries. The parser parses user preferences to derive a vector function having attribute values and ascertains relevant attribute sets for the user preferences. The processor receives the user preferences from a user device, ranks and weights the attribute values based on encoded preference information derived from the user preferences, associates values to the feasible travel itineraries, and transmits the feasible itineraries to the user device to present a multiattributed travel itinerary to visualize itinerary information associated with each of the travel attributes.