Chatbot Search Refinement Protocol for Travel Itineraries
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Solution Overview
Problem
Current travel booking engines are complex and produce numerous results, leading to frustration for users, repeated queries, and wastage of network traffic and server resources.
Innovation Solution
A method involving a natural language conversation with a client device to generate parameters, parse them into portions using a refinement protocol, and send them to travel-actor engines for search, transforming raw outlines into travel itineraries based on the conversation and criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional travel booking engines are used, then comprehensive search results can be obtained, but the system complexity increases and user frustration increases due to too many results
Solution Approach 1:
The patent segments the travel search process into distinct phases: initial broad search using unstructured parameters, followed by refinement phases with structured parameters. The search results are segmented from raw comprehensive data into refined, curated itineraries that present only essential information to users, reducing complexity while maintaining comprehensiveness.
Solution Approach 2:
The patent introduces an intermediary refinement engine that acts as a mediator between the comprehensive search results and the user. This intermediary processes raw search data, applies refinement protocols, and presents simplified itineraries, thereby reducing user-facing complexity while preserving search comprehensiveness.
2Productivity
If traditional travel booking engines are used, then search results are generated, but network traffic congestion and server resource drain occur due to repeated queries
Solution Approach 1:
The patent performs preliminary parsing and structuring of search parameters before executing searches. By pre-processing unstructured natural language into structured search criteria, the system reduces the need for repeated clarification queries, thereby reducing network traffic and server load from redundant search operations.
Solution Approach 2:
The patent implements feedback loops where the system monitors search patterns and user responses, continuously refining its parameter extraction and structuring processes. This feedback mechanism reduces repeated queries by learning from previous interactions, thereby conserving network traffic and server resources.
3Ease of operation
If unstructured natural language parameters are used for search, then user interaction is simplified, but parameter parsing and processing complexity increases
Solution Approach 1:
The patent introduces an intermediary natural language processing layer that bridges simple user input and complex search requirements. This intermediary automatically parses unstructured language into structured parameters, maintaining ease of user interaction while managing parsing complexity within the system.
Solution Approach 2:
The patent replaces manual parameter structuring with automated natural language processing and machine learning models. This substitution handles the complexity of parsing unstructured language automatically, keeping user interaction simple while managing processing complexity through intelligent automation.
Data Source
AI summary
The present specification provides, amongst other things, a novel system, method and apparatus for real time searches. A search engine is provided that generates search parameters based on a natural language conversation with a chatbot. The parameters are parsed into a plurality of portions according to a refinement protocol. At least one of the portions is sent to a first engine for a search, and the results of are transformed using the refinement protocol.