Domain-Name Framework for Digital Assistant Entity Resolution
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Solution Overview
Problem
Current bot assistants lack precision in identifying entities and responders, leading to imprecise and incomplete responses to natural language requests, as they are hardwired to match keywords and cannot aggregate information from multiple responders effectively.
Innovation Solution
A domain-name based framework that uses unique identifiers to interpret and process natural language requests, enabling digital assistants to accurately identify entities and responders, and aggregate responses from multiple sources by generating requests based on ontology-defined syntax.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If bot assistants use hardwired keyword matching to identify entities, then the system structure remains simple, but the precision in identifying entities deteriorates
Solution Approach 1:
The patent introduces an intermediary component (entity resolution service/layer) that sits between the simple keyword matching system and the entity identification process. This intermediary resolves entity references by matching keywords against known entity databases, thereby improving entity identification precision without requiring a complete redesign of the system architecture.
Solution Approach 2:
The system enables responders to self-register and self-describe their capabilities through standardized interfaces. Responders automatically provide metadata about the entities they can handle, allowing the digital assistant to autonomously build its entity knowledge base without manual configuration, thus improving precision while keeping system complexity manageable.
2Loss of information
If bot assistants are hardwired to match keywords with single responders, then the response time remains fast, but the completeness of information aggregation deteriorates
Solution Approach 1:
The patent implements a dynamic responder selection mechanism that adapts based on the query. Instead of static hardwired mappings, the system dynamically determines which responders to invoke by analyzing the query intent and matching it against responder capabilities. Multiple responders can be dynamically selected and coordinated to provide complete information aggregation.
Solution Approach 2:
The patent creates a universal interface layer that allows multiple responders with different specializations to be accessed through a common standard. This universal architecture enables a single digital assistant to efficiently coordinate multiple responders for different aspects of a query, ensuring information completeness without sacrificing productivity through standardized communication protocols.
3Adaptability or versatility
If bot assistants require specialized applications for each responder integration, then the integration precision improves, but the ease of integration deteriorates
Solution Approach 1:
The patent segments the integration process into independent, modular components. Each responder implements a standardized interface that separates its core functionality from integration concerns. This segmentation allows responders to be integrated independently through common protocols, providing both precision in functionality and ease of integration through modularity.
Solution Approach 2:
The patent changes the integration parameters from custom-built specialized applications to standardized interface implementations. By defining standard communication protocols and data formats, the system allows responders to be integrated by implementing parameterized interfaces rather than requiring custom application development, thereby improving both adaptability and ease of integration.
Data Source
AI summary
In one embodiment, a domain-name based framework implemented in a digital assistant ecosystem uses domain names as unique identifiers for request types, requesting entities, responders, and target entities embedded in a natural language request. Further, the framework enables interpreting natural language requests according to domain ontologies associated with different responders. A domain ontology operates as a keyword dictionary for a given responder and defines the keywords and corresponding allowable values to be used for request types and request parameters. The domain-name based framework thus enables the digital assistant to interact with any responder that supports a domain ontology to generate precise and complete responses to natural language based requests.