Context-Aware Terminology Suggestion System for Enterprise Knowledge
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Solution Overview
Problem
In enterprises, new employees and those unfamiliar with domain-specific vocabularies face inefficiencies in discovering term meanings, leading to reduced productivity due to reliance on inefficient methods like internet searches, emails, and phone calls.
Innovation Solution
A computer-implemented method that identifies terms in digital documents, retrieves definitions and related resources, and visually displays this information within the user interface, utilizing a distributed computer system with a text processor and generative artificial intelligence model to provide context-aware suggestions and tone adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If employees use traditional methods (internet searches, emails, phone calls) to discover term meanings, then they can obtain information, but productivity is reduced due to time consumption and inefficiency
Solution Approach 1:
The system pre-processes and stores domain-specific terminology, definitions, and related information in a structured knowledge base before employees need it. When a term is encountered in a document, the system can immediately retrieve pre-prepared information without requiring employees to conduct searches, thus providing immediate access to term meanings while maintaining high productivity
Solution Approach 2:
The patent introduces an intermediary system (the terminology management system with knowledge base) that mediates between employees and domain-specific information. Instead of employees directly searching through various sources, the intermediary system automatically retrieves and presents relevant term definitions and information, eliminating the need for traditional search methods and improving both information access and productivity
2Loss of information
If employees conduct searches, send emails, or make phone calls to understand terms, then they can obtain definitions and resources, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary organization and indexing of domain-specific knowledge, including term definitions, related documents, and expert contacts, before they are needed. This pre-processing enables instant retrieval when terms are encountered, eliminating the time-consuming search process while ensuring comprehensive information is available
Solution Approach 2:
The system enables self-service information retrieval where employees can automatically obtain term definitions and related information by simply interacting with the system interface. The system autonomously searches the knowledge base, retrieves relevant information, and presents it to employees without requiring them to manually contact colleagues or conduct extensive searches, thus reducing time loss while maintaining comprehensive information access
Data Source
AI summary
In one embodiment, a method may receive, from a client device, a text input from a user. The text input can comprise a plurality of words. The method can access, from a server computer, common knowledge associated with a data store. The method can generate, using a generative artificial intelligence model, contextual features in a query associated with the text input. The generative artificial intelligence model has been trained to generate the contextual features in the query based on the common knowledge associated with the data store. The method can generate, using the generative artificial intelligence model, a text output using the contextual features in the query associated with the text input. The method can send, to the client device, instructions for presenting a user interface comprising the text output.