Natural Language Bet Search Using Embedding-Based Match Generation
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Solution Overview
Problem
Existing bet search systems are complex and not user-friendly, requiring users to scroll through long lists of potential bets and lacking the ability to search for trending events on social media, making it difficult for consumers to find their desired bets.
Innovation Solution
A system utilizing a language processing engine to translate natural language queries into computer-readable data points, a bet engine to determine and generate bets, and a machine learning model to match embeddings, allowing for intelligent bet searching and real-time data integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static list of all possible bets is provided, then users have comprehensive options, but users must scroll through a long list to find their desired bet, increasing search time and complexity
Solution Approach 1:
The patent introduces an intermediary search system that includes a language processing engine and bet engine. This intermediary layer translates user natural language queries into computer-readable data points and matches them against the comprehensive bet database, eliminating the need for users to manually scroll through long lists while maintaining access to all bet options.
Solution Approach 2:
The patent replaces the mechanical manual scrolling through lists with an automated AI-driven search system. The language processing engine and machine learning models automatically process queries and retrieve relevant bets, substituting the manual mechanical process with an intelligent automated system that reduces search time significantly.
2Adaptability or versatility
If traditional search systems are used, then the system structure is simple, but the system lacks the ability to search for trending events on social media and intelligent bet matching
Solution Approach 1:
The patent implements a multi-functional search system where the language processing engine can handle various query types (natural language, trending events, social media data) and the bet engine can perform multiple matching operations. This universal approach allows the system to provide intelligent bet searching capabilities while managing complexity through integrated design.
Solution Approach 2:
The system employs self-service mechanisms where the machine learning models automatically learn from data and improve their matching capabilities without manual reconfiguration. The language processing engine automatically translates and processes queries, reducing the need for complex manual system configuration while maintaining advanced search capabilities.
3Ease of operation
If users manually search through bets, then the system remains simple, but the user experience is not user-friendly and consumers cannot easily find desired bets
Solution Approach 1:
The patent introduces an intermediary AI-driven search layer that translates user-friendly natural language queries into precise search operations. This intermediary system handles the complexity of matching algorithms and data processing, presenting a simple and intuitive interface to users while maintaining sophisticated underlying capabilities.
Data Source
AI summary
Systems, methods, and computer-readable media for presenting one or more bets to a user based on a natural language query received from the user. In some embodiments, a natural language query from a user may be received. The natural language query may be translated into computer-readable data by a language processing engine. The language processing engine may use a large language model to translate the natural language query into computer-readable data. The computer-readable data may be in the form of an embedding. A bet engine may match the computer-readable data to a bet when the bet and the computer-readable data exceed a predetermined threshold with regard to similarity. The bet engine may generate a new bet corresponding to the computer-readable data. The system may then present the bet to the user.