Context-Aware Conversational Assistant Hybrid Architecture
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Solution Overview
Problem
Existing conversation systems either rely on human agents, which are slow and sometimes inaccurate, or automated systems, which struggle to parse free-form queries due to lack of context and user history.
Innovation Solution
A hybrid, context-aware conversational assistant that combines human agent interaction with automated information retrieval, using info cards to present pregenerated responses based on user queries and historical data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a human agent is used to interact with the user, then accuracy in determining user information needs is improved, but response speed deteriorates
Solution Approach 1:
The patent introduces an automated system as an intermediary between the user and human agent. This automated system handles initial query parsing and information retrieval, allowing the human agent to focus on complex interpretation and decision-making. The automated component processes routine tasks at high speed while the human agent provides accuracy-critical judgment, thus resolving the speed-accuracy tradeoff.
Solution Approach 2:
The patent divides the conversation system into distinct functional segments: an automated system component for parsing queries and retrieving information, and a human agent component for interpreting user needs and formulating responses. This segmentation allows each component to operate in its optimal performance zone, with the automated system handling speed-critical tasks and the human agent handling accuracy-critical tasks.
2Speed
If an automated system is used to retrieve information, then response speed is improved, but ability to parse free-form queries deteriorates
Solution Approach 1:
The patent implements preliminary action by having the automated system pre-process and structure user queries before they reach the human agent. The automated component performs initial parsing, categorization, and information gathering, preparing structured data that makes subsequent human processing more efficient. This preliminary structuring enables the automated system to handle speed-critical preprocessing while reducing the complexity of free-form query interpretation for the human agent.
3Productivity
If a hybrid system is implemented to combine human and automated components, then overall productivity is improved, but system complexity increases
Solution Approach 1:
The patent merges the strengths of human agents and automated systems into a unified hybrid architecture. The automated system handles query parsing, information retrieval, and initial response drafting, while the human agent handles interpretation, validation, and final response formulation. This merging creates a synergistic system where the whole is greater than the sum of its parts, achieving high productivity through coordinated human-automated collaboration.
Data Source
AI summary
Method and media for an interface for a context-aware conversational assistant. A hybrid system is disclosed that can take advantage of both a human agent's facility at interacting with the user and an automated system's speed and accuracy at information retrieval to quickly and accurately provide the user with the needed information. In response to a user query, the conversational assistant determines one or more responses that may be relevant and presents them in the chat window to the agent. If the conversational assistant correctly interpreted the question, the agent can quickly respond to the query using the pregenerated response. Otherwise, the agent can edit a pregenerated response or compose a new response from scratch.