Bot Service System for Personalized Natural Language Search
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Solution Overview
Problem
Current messaging systems lack efficient methods for users to interact with network-accessible services within a familiar messaging context, and there is a need for improved techniques to recommend and configure messaging bots based on user intent and service requirements.
Innovation Solution
The system includes a bot-service system that receives user service prompts in natural language, matches them against bot capability catalogs, and identifies relevant bots for user devices, using natural-language machine-learning components to determine bot relevancy and update interaction histories for improved bot suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If natural language matching is used to identify bots, then user interaction ease is improved, but system complexity increases
Solution Approach 1:
The patent introduces a bot-service system as an intermediary layer between users and network services. This system maintains bot capability catalogs that map natural language prompts to specific bots, allowing users to interact with services through familiar messaging without directly managing the underlying service complexity. The intermediary handles the matching and routing, simplifying user interaction while containing system complexity within the service layer.
Solution Approach 2:
The system creates simplified copies of service interfaces through bot capability catalogs. Instead of requiring users to navigate complex service configurations, the system maintains natural language representations (copies) of service capabilities that users can interact with using everyday language. These catalogs serve as simplified models that replicate essential service functions in user-friendly formats.
2Reliability
If personalized bot recommendations are provided, then user experience is improved, but information processing requirements increase
Solution Approach 1:
The system performs preliminary action by pre-processing and storing bot capability information in structured catalogs before users need them. Bot capabilities, service requirements, and matching criteria are prepared in advance and organized in bot-service system databases. When users interact with the system, the matching process queries pre-processed information rather than analyzing everything from scratch, reducing real-time information processing requirements while maintaining personalized recommendation quality.
3Adaptability or versatility
If multiple user services are integrated, then service versatility is improved, but system complexity increases
Solution Approach 1:
The bot-service system implements universality by creating a single platform that handles multiple user services through a common architecture. The system uses unified bot capability catalogs and standardized matching processes that work across different service types (messaging, reservations, information queries, etc.). This multi-functional approach allows diverse services to be integrated through consistent mechanisms rather than requiring separate systems for each service, managing complexity through standardization.
Data Source
AI summary
Techniques for personalized search for bots are described. In one embodiment, an apparatus may comprise a client communication component operative to receive a user service prompt from a user client device at a bot-service system, the user service prompt expressed in natural language and identify two or more filtered bots to the user client device in response to receiving the user service prompt from the user client device; and an interaction processing component operative to determine two or more selected bots of a plurality of bots and determine the two or more filtered bots of the two or more selected bots based on bot relevancy. Other embodiments are described and claimed.