Fare Analytic Engine Using Graph Database for Pricing Queries

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Solution Overview

Problem

Conventional pricing systems for travel and cargo fares face inefficiencies in processing requests due to the complexity of analyzing multiple factors such as flight schedules, availability, published fares, and business logic, leading to significant computing resource expenditure and delayed responses.

Innovation Solution

A fare analytic engine utilizing a graph database to represent and process fare and fare-related data, allowing for efficient querying and retrieval of pricing solutions by creating nodes, relationships, and applying properties to nodes and relationships, enabling faster data manipulation and query processing.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional pricing systems process pricing queries by analyzing multiple factors including flight schedules, availability, published fares, and business logic, then comprehensive pricing solutions can be obtained, but response time exceeds 30 seconds and computing resources are excessively consumed

Engineering Contradiction:

Improvepricing solution accuracyVSAvoidresponse time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The pricing system is divided into multiple independent components: graph database engine for data storage and retrieval, pricing rule engine for business logic evaluation, and query processing module. This segmentation allows each component to operate independently and efficiently, reducing overall processing time while maintaining comprehensive pricing analysis capabilities

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Fare data, flight schedules, availability information, and business rules are pre-processed and stored in graph database structures before query execution. This preliminary organization of data enables rapid retrieval and analysis during actual pricing queries, eliminating the need to process raw data in real-time and significantly reducing response time

Inventive Principle:

Principle #10Preliminary action

2Loss of information

If conventional systems traverse large volumes of fare and fare-related data to process database queries, then complete pricing information can be retrieved, but substantial data processing challenges and computing resource expenditure occur

Engineering Contradiction:

Improvefare data completenessVSAvoidcomputing resource consumption

Core Design Contradiction:

Loss of informationVSUse of energy by moving object

Solution Approach 1:

A graph database serves as an intermediary layer between raw fare data and the pricing query processing system. The graph database pre-organizes fare data, flight information, and business rules into efficient queryable structures, acting as a mediator that reduces the computational burden on the pricing engine while ensuring complete fare information is available for processing

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system transforms fare data from traditional relational database formats into graph database structures with nodes representing fares, flights, and routing information, and edges representing relationships between them. This parameter change in data organization enables efficient traversal and querying, reducing computing resource consumption while maintaining data completeness

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If pricing systems use specialized techniques to review fare offerings across multiple vendors and return ranked results, then customer-specific pricing solutions can be provided, but system complexity increases

Engineering Contradiction:

Improvevendor fare comparison capabilityVSAvoidsystem architecture complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The graph database structure and pricing engine are designed to handle multiple vendor fare offerings through a unified framework. The same graph query mechanisms and pricing rules apply regardless of the number or type of vendors, providing versatile vendor comparison capability without requiring separate processing systems for each vendor, thus avoiding increased complexity

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10032195B2System, method and computer program product for providing a fare analytic engine

Publication Date: 2018.07.24 AIRLINE TARIFF PUBLISHING CO

AI summary

An exemplary embodiment of a system, method and/or computer program product for creating a fare analytic database, may include: receiving, by at least one processor, fare(s) and fare related data; and creating a graph database of the fare(s) and fare related data; where the creating may include: creating one or more node(s) of the graph database representing at least one component of the fare and fare related data; creating one or more relationship(s) between a plurality of the nodes; and applying at least one property to the node(s) and the relationship(s). A fare analytic engine may further incorporate the database, and the engine may process queries traversing the database for fare and fare related data; and functional programming methods may be used to generate Boolean byte code routines from fare restrictions, according to exemplary embodiments disclosed.