Domain-Adapted Digital Assistant for Screening Services
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Solution Overview
Problem
Voice- or text-based digital assistants often fail to provide accurate and efficient results in handling tasks such as web searching and navigation due to their inability to understand domain-specific vocabulary and user intent effectively.
Innovation Solution
A server system equipped with an intelligent assistant, named 'Emma', that understands screening domain vocabulary and idioms, senses user intent, and enables screening services by interacting with users through speech or text interfaces, utilizing machine-driven language translation and natural language processing to provide seamless and secure access to screening services, including background checks and due diligence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional voice- or text-based digital assistants are used to handle tasks such as web searching and navigation, then basic functionality is provided, but accuracy and efficiency deteriorate due to inability to understand domain-specific vocabulary and user intent
Solution Approach 1:
The patent transforms the digital assistant from a generic task-handling system to a domain-specific screening assistant by changing key parameters: incorporating domain-specific vocabulary and idioms into the language model, adding screening-specific entities and relationships to the knowledge graph, and configuring the system to understand screening domain context. These parameter changes enable the assistant to accurately interpret screening-related queries and provide precise results.
Solution Approach 2:
The patent introduces an intermediary layer between the user query and the task execution: a screening-domain-adapted language model that translates natural language queries into structured screening intents, and a knowledge graph that mediates between the intent and relevant screening services. This intermediary layer enables accurate understanding of domain-specific vocabulary and user intent before executing tasks.
2Measurement precision
If the digital assistant is enhanced to understand domain-specific vocabulary and user intent, then accuracy improves, but system complexity increases
Solution Approach 1:
The patent segments the digital assistant system into distinct modular components: a domain-adapted language model for understanding queries, a knowledge graph for storing screening domain knowledge, an intent recognition module for identifying user goals, and a task execution module for performing actions. This segmentation allows each component to be optimized independently while maintaining overall system accuracy.
Solution Approach 2:
The patent creates a multi-functional screening assistant that can handle various screening-related tasks (web searching, navigation, information retrieval, service access) through a single unified system. The domain-adapted language model and knowledge graph serve multiple functions across different tasks, reducing overall system complexity compared to having separate specialized systems for each function.
Data Source
AI summary
In one aspect, a server that receives, from a client terminal via a network, a request to initiate a verbal conversation using natural language that is in a spoken or textual format, extracts information during the verbal conversation, determines a context of the verbal conversation, receives an inquiry during the verbal conversation, processes the inquiry, acquires response information based on the determined appropriate response, and transmits to the client terminal the response information.