NLP Human Interaction System for Adaptive Business Decision Making
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Solution Overview
Problem
Current human-machine interaction systems lack the ability to understand user decision-making processes and adapt information retrieval to user-specific goals, leading to inefficient business decision-making.
Innovation Solution
A human interaction system that uses natural language processing to extract keywords from user questions, displays relevant metadata, and nudges users with predefined questions based on demographic profiles to identify business opportunities, employing a processor with modules for receiving, extracting, displaying, and analyzing data to provide strategic insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If electronic machines are used to provide information for decision making, then information retrieval speed is improved, but understanding of user decision-making processes and user-specific goals deteriorates
Solution Approach 1:
The patent introduces a natural language processing intermediary that mediates between the user's instinctive decision-making process and the machine's information retrieval capability. The NLP system translates user intentions into structured queries while preserving the contextual understanding of user goals, enabling both fast information retrieval and adaptive understanding of decision-making processes.
2Device complexity
If traditional user interfaces are used for human-machine interaction, then system complexity is reduced, but decision-making efficiency deteriorates
Solution Approach 1:
The system employs self-service natural language processing that automatically understands and processes user intentions without requiring complex interface interactions. The NLP capability enables the system to autonomously interpret user goals, extract relevant information needs, and retrieve data efficiently, thereby improving decision-making efficiency while keeping the interface simple.
3Device complexity
If generic information retrieval is used, then system complexity is minimized, but identification of business opportunities and tailored strategies deteriorates
Solution Approach 1:
The patent applies preliminary action by using natural language processing to pre-analyze and structure user queries before information retrieval. The system预先 extracts user intentions, identifies relevant context, and formulates targeted search strategies, ensuring that user-specific goals and context are preserved while maintaining relatively simple system architecture.
Data Source
AI summary
Disclosed is a method for displaying a strategy, pertaining to a business opportunity, during a conversation with a user. Initially, a question is received from a user. Upon receiving, a set of keywords from the question is extracted based on natural language processing techniques. Subsequently, an answer to the question is displayed along with metadata associated to the answer. The metadata is displayed based on a demographic profile of the user. Further, the user is nudged with a set of predefined questions based on the demographic profile and the set of keywords. Furthermore, a set of responses received against the set of predefined questions is analyzed to identify a business opportunity. The set of responses is analyzed based on the set of keywords and the demographic profile. In addition, a strategy pertaining to the business opportunity is displayed based on the question, the set of responses, and the demographic profile.