Domain-Specific Query Handlers for Dialog System Resource Allocation
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Solution Overview
Problem
Existing automated dialog systems face inefficiencies due to redundant data storage and resource allocation issues, as they lack distinction between frequently and infrequently used information, leading to suboptimal resource utilization and increased response times.
Innovation Solution
A method and system that split user queries into sub-queries based on domain-specific keywords, retrieving responses from hierarchically arranged Domain-specific Query Handlers (DQHs) optimized by resource availability, network bandwidth, and query frequency, allowing for optimal resource allocation and faster response generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple copies of data are stored in each dialog system to support concurrent queries, then query handling capability is improved, but resource consumption and redundancy increase
Solution Approach 1:
The patent merges multiple dialog systems into a unified architecture where a single centralized database stores data copies that are shared across all dialog systems. This eliminates the need for each individual dialog system to maintain its own separate data copies, thereby reducing overall redundancy while maintaining the ability to handle concurrent queries from multiple users.
2Reliability
If resources are allocated equally to all dialog systems, then each system can handle queries independently, but resource utilization efficiency decreases
Solution Approach 1:
The patent creates a universal resource pool that serves all dialog systems simultaneously. Instead of allocating dedicated resources to each individual dialog system, the system implements a shared resource architecture where a single database and resource pool can be accessed by multiple dialog systems, enabling one resource to serve multiple functions and users.
Solution Approach 2:
The patent combines separate resource allocations into a unified shared resource pool that is accessible by all dialog systems. This merging allows resources to be dynamically shared and allocated based on actual demand rather than static pre-allocation, improving overall utilization efficiency while maintaining system reliability.
3Ease of operation
If all data is treated equally in resource allocation, then simplicity is maintained, but response time for frequently accessed data increases
Solution Approach 1:
The patent implements local quality by differentiating resource allocation based on data characteristics. Frequently accessed data is allocated premium resources such as cached memory and high-speed access paths, while less frequently accessed data uses standard storage resources. This creates quality variations in different parts of the system matched to actual usage patterns.
Solution Approach 2:
The patent performs preliminary action by proactively caching frequently accessed data in high-speed memory before it is actually needed. The system monitors access patterns and pre-loads data into cached memory, so when users query this data, the response time is minimized because the data is already in a ready state.
Data Source
AI summary
Disclosed herein is method and system for providing domain-specific response to user query. The user query is split into one or more sub-queries and domain of each of the sub-queries is determined based on domain-specific keywords present in each of the sub-queries. One or more responses to each of the sub-queries is retrieved from corresponding Domain-specific Query Handlers (DQHs). Finally, each of the one or more responses are collated for providing the domain-specific query to the user. In an embodiment, the DQHs are hierarchically arranged based on their importance and relevance to the user query. Further, the resources are allocated to each of the DQHs based on their hierarchy, thereby optimally distributing the resources among the DQHs. In an embodiment, the method of present disclosure ensures completeness/sufficiency in the response, before collating the one or more responses and providing the domain-specific response to the user.