Dialog Intent Disambiguation Using Domain Models and Generic Rules
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Solution Overview
Problem
Existing dialog systems struggle to efficiently handle dialog inputs with multiple ambiguous intents, requiring complex and time-consuming manual rule-based configurations to manage granular rules for intent prioritization, disambiguation, and follow-up conversations.
Innovation Solution
A domain model-driven approach that identifies ambiguous intents within a dialog system input and leverages an accessible domain model to determine relevant annotated themes, using a set of generic rules to guide the dialog system in generating conversations, simplifying decisions on disambiguation and follow-up recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a dialog system uses traditional rule-based approaches to handle ambiguous intents, then it can achieve accurate disambiguation, but the system complexity increases significantly due to the large number of granular rules required
Solution Approach 1:
The patent segments the complex rule-based system into modular components: a domain model layer that defines semantic relationships between intents, and a rule engine layer that applies generic rules. This segmentation allows the system to handle ambiguous intents through structured domain knowledge rather than numerous granular rules, reducing overall system complexity while maintaining disambiguation accuracy.
Solution Approach 2:
The patent introduces a domain model as an intermediary layer between the dialog system input and the rule engine. This domain model contains annotated themes and semantic relationships that mediate the processing of ambiguous intents, allowing the system to resolve ambiguities through structured knowledge representation rather than direct rule application, thereby reducing the number of granular rules needed.
2Reliability
If a dialog system implements comprehensive rules for handling all possible dialog scenarios, then it can improve dialog processing accuracy, but the ease of operation and maintenance deteriorates
Solution Approach 1:
The patent creates universal generic rules that can handle multiple dialog scenarios through the domain model framework. Instead of implementing specific rules for each possible dialog situation, the system uses annotated themes and semantic relationships in the domain model to enable a smaller set of generic rules to address diverse intents, improving ease of operation and maintenance while maintaining processing accuracy.
Solution Approach 2:
The patent changes the parameters of the rule system by shifting from granular, scenario-specific rules to generic rules that operate on domain model parameters. The domain model contains configurable elements like annotated themes and semantic relationships that can be adjusted to handle different dialog scenarios, making the system easier to operate and maintain while preserving accuracy.
3Device complexity
If a dialog system uses a simplified rule set to reduce complexity, then the ease of operation improves, but the ability to handle ambiguous intents effectively deteriorates
Solution Approach 1:
The patent performs preliminary action by pre-defining the domain model with annotated themes and semantic relationships before the dialog processing occurs. This preparatory structuring of knowledge allows a simplified rule set to effectively handle ambiguous intents, as the domain model already contains the necessary semantic information to guide disambiguation without requiring complex rules.
Solution Approach 2:
The domain model serves as an intermediary that bridges the gap between simple generic rules and complex ambiguous intent handling. It contains pre-structured semantic knowledge that mediates between the simplified rule set and the nuanced requirements of ambiguous intent disambiguation, enabling effective handling with reduced complexity.
4Productivity
If a dialog system employs extensive granular rules to cover all dialog cases, then the productivity and coverage improve, but the time required for system configuration and maintenance increases
Solution Approach 1:
The patent implements universal generic rules that can handle multiple dialog cases through the domain model framework. This approach maintains comprehensive dialog handling coverage while reducing configuration and maintenance time, as changes to the domain model can affect multiple rule applications simultaneously rather than requiring individual rule modifications.
Solution Approach 2:
The patent merges multiple granular rules into a smaller set of generic rules that operate on domain model structures. This consolidation maintains comprehensive coverage by leveraging the semantic relationships in the domain model, while significantly reducing the time required for configuration and maintenance through fewer rules to manage.
Data Source
AI summary
An embodiment for domain model driven processing of dialog system inputs including ambiguous intents. The embodiment may receive a dialog system input for processing by a dialog system. The embodiment may identify a series of ambiguous intents within the received dialog system input. The embodiment may, in response to identifying the series of ambiguous intents, determine, based on an accessible domain model, one or more relevant annotated themes corresponding to each individual intent within the series of ambiguous intents. The embodiment may execute, using the dialog system, a dialog corresponding to the received dialog system input by employing a set of generic rules, wherein the set of generic rules leverage the identified relevant annotated themes.