Dynamic Free-Text Search Database for Travel Suggestions
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Solution Overview
Problem
Current travel suggestion systems are limited by their reliance on predefined formats and types of trip parameters, which restrict user input and flexibility in search queries, making it difficult for users to efficiently find travel options that match their generalized preferences.
Innovation Solution
A dynamic free-text search database system that processes natural language queries by generating relationships between keywords, trips, and weight values, allowing for the calculation of updated weight values based on user interactions and online resources, enabling the system to provide relevant travel suggestions without the need for predefined formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If predefined formats and types of trip parameters are used in the GUI, then the system structure is simple and easy to implement, but user input flexibility and search query versatility are restricted
Solution Approach 1:
The patent implements a dynamic free-text search database where weight values for keywords are continuously updated based on user interactions and search patterns. The system transitions from static predefined parameters to dynamic free-text processing, allowing the database structure to adapt and evolve based on usage patterns while maintaining operational simplicity through automated weight calculation algorithms.
Solution Approach 2:
The system changes the parameter representation from fixed formatted fields to flexible free-text keywords with dynamic weight values. Each keyword is assigned a weight that reflects its relevance based on user behavior, allowing the system to handle diverse user inputs without requiring predefined formats while managing complexity through parameter-based relevance scoring.
2Ease of operation
If free-text search requests are processed without predefined formats, then user input flexibility is improved, but the complexity of processing and analyzing search queries increases
Solution Approach 1:
The system implements self-service through automated weight value calculation based on user interactions. The database automatically updates keyword weights by analyzing search patterns and user behavior without requiring manual intervention or complex preprocessing of free-text queries. This allows the system to handle unstructured user input conveniently while managing processing complexity through automated relevance scoring.
Solution Approach 2:
The system uses feedback from user interactions to dynamically update keyword weight values. By analyzing search patterns and user behavior, the system continuously refines the relevance scoring of keywords, enabling efficient processing of free-text queries without predefined formats while keeping complexity manageable through data-driven optimization.
3Reliability
If static weight values are used in the database relationships, then the database structure is simple and fast to query, but the relevance and accuracy of travel suggestions deteriorate over time
Solution Approach 1:
The patent implements dynamic weight values that automatically update based on user interactions and search patterns. The system transitions from static to dynamic weighting, where keyword relevance is continuously refined based on actual usage data. This maintains high suggestion accuracy over time while managing update complexity through automated algorithms that process user behavior data.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing weight values in the database relationships. These weight values are updated in advance based on accumulated user interaction data, allowing the system to maintain high query performance while incorporating dynamic relevance information without requiring complex real-time calculations during user searches.
4Reliability
If the database is updated frequently with new weight values, then the relevance of suggestions is maintained, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary updates by calculating and storing weight values in advance based on accumulated user interaction data. Rather than processing updates in real-time during user searches, the system pre-computes weight adjustments and incorporates them into the database structure beforehand, maintaining suggestion relevance while avoiding time-consuming processing during user queries.
Data Source
AI summary
Systems, methods, and computer program products for implementing a dynamic free-text search database. First data is generated for the dynamic free-text search database that represents a first relationship including a first keyword, a first trip, and a first weight value. A plurality of free-text search requests are received, and a second weight value for the first relationship is calculated based on the free-text search requests. The second weight value differs from the first weight value. The first data is transformed into second by inserting the second weight value into the first data such that the first relationship includes the second weight value.