Automated Assistant Date Time Constraint Inference
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Solution Overview
Problem
Automated assistants often fail to correctly understand and process user requests with vague date and time constraints, leading to user frustration and increased computational resources.
Innovation Solution
The system identifies atomic elements of temporal constraints, converts them into specific mathematical structures exhibiting periodicity, and combines these using set mathematics operations to enhance understanding and reduce computational resources, enabling equivalence inference and simplified constraint processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the automated assistant processes vague date and time constraints using traditional methods, then it can handle basic requests, but it fails to correctly understand and process requests with vague temporal constraints
Solution Approach 1:
The patent segments vague temporal constraints into atomic elements (e.g., breaking down 'next week in the afternoon' into discrete temporal components). This segmentation allows the system to process each element systematically using set mathematics operations, improving understanding accuracy without requiring overly complex overall system architecture.
Solution Approach 2:
The patent transforms temporal constraints from natural language expressions into mathematical parameters and periodic sets. By changing the representation format from vague text to structured mathematical objects, the system achieves precise processing of temporal constraints while maintaining manageable system complexity through standardized transformation rules.
2Loss of energy
If the automated assistant uses traditional processing methods for temporal constraints, then the system structure remains simple, but computational resources are increased
Solution Approach 1:
The patent creates periodic set representations as mathematical copies of temporal constraints. These copied representations can be manipulated using efficient set mathematics operations rather than processing the original natural language expressions repeatedly, reducing computational resource consumption while improving processing efficiency.
Solution Approach 2:
The patent performs preliminary transformation of temporal constraints into periodic sets before main processing operations. This preliminary action structures the data in advance, enabling more efficient subsequent processing and reducing overall computational resource requirements while enhancing productivity.
3Adaptability or versatility
If the automated assistant processes temporal constraints without equivalence inference, then the processing steps are straightforward, but the ability to understand vague constraints is limited
Solution Approach 1:
The patent merges multiple temporal constraint representations into unified periodic sets through set mathematics operations. This merging capability enables equivalence inference by allowing the system to combine and compare different temporal expressions systematically, enhancing interpretation capability while keeping the inference mechanism manageable through mathematical unification.
Data Source
AI summary
A method includes receiving an utterance at a computerized automated assistant system, and detecting, via a date/time constraint module of the computerized automated assistant system, one or more constraints in the utterance associated with a date or time. The utterance is associated with a domain. The method further comprises generating, via the date/time constraint module, a periodic set for each of the one or more constraints associated with the date or time, and combining, via the date/time constraint module, the one or more periodic sets. The method further comprises processing, via a dialogue manager module of the computerized automated assistant system, the combined periodic sets to determine an action, and executing the action at the computerized automated assistant system.