Natural Language Interface for Workspace Analytics Query Matching
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Solution Overview
Problem
Workspace analytics systems require significant training for users to effectively navigate and utilize their complex data and tools, posing a barrier for those without technical expertise, as they must adapt to technical interfaces rather than interacting in natural language.
Innovation Solution
A computer-implemented method providing a natural language interface that processes user queries by associating pattern-form questions with answer definitions, allowing users to interact with the system using natural language queries, which are then matched to retrieve relevant information from the workspace analytics system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a complex workspace analytics system with extensive data and tools is provided, then the system's functionality and information availability are improved, but the difficulty of operation and training requirements increase for users
Solution Approach 1:
The patent introduces a natural language interface as an intermediary layer between users and the complex workspace analytics system. This interface includes a question parser that translates natural language questions into system queries, and an answer generator that presents results in natural language. This mediator shields users from the underlying system complexity while maintaining full access to the system's analytical capabilities.
Solution Approach 2:
The patent replaces the traditional mechanical interaction model (clicking through menus, navigating interfaces, selecting parameters) with a natural language processing system. Users can ask questions in plain English rather than navigating complex UI elements, substituting the mechanical interaction paradigm with a linguistic one that is more intuitive and requires less training.
2Reliability
If traditional technical interfaces are used, then the system can process and deliver accurate information, but users must adapt to technical terms and interfaces rather than using natural language
Solution Approach 1:
The patent inverts the traditional information retrieval approach. Instead of requiring users to formulate technical queries based on system parameters and navigate to specific data sources, the system parses natural language questions and automatically generates the appropriate technical queries and navigation paths. This inversion maintains information accuracy while reversing the adaptation burden from user-to-system to system-to-user.
3Productivity
If extensive training is provided to users, then their ability to utilize the system effectively is improved, but the time and resources required for training increase
Solution Approach 1:
The natural language interface enables users to immediately access system capabilities without requiring formal training. The system adapts to the user's natural language patterns and provides relevant information directly in response to their questions, eliminating the need for structured training programs while maintaining high user effectiveness.
Data Source
AI summary
A method includes associating, for each one of a plurality of answer definitions, at least one or more pattern-form questions, wherein each answer definition has an associated jump target that defines a respective entry point into the workspace analytics system to provide information responsive to the associated one or more pattern-form questions. The method further includes receiving a user input including capturing input text defining a natural language user query, matching the received input text to one of the pattern-form questions thereby selecting the jump target associated with the matched pattern-form question, and generating a response to the natural language user query by retrieving information from the workspace analytics system by referencing a link based on the selected jump target and zero or more parameters values.