Autonomous Agent Conclusive Answer Generation via Syntactic Parse Trees
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Solution Overview
Problem
Existing solutions for interactive sessions with autonomous agents fail to provide comprehensive answers, instead offering short replies derived from traditional search indexes, which are not responsive to multiple user utterances.
Innovation Solution
The method involves generating conclusive answers using syntactic parse trees by accessing seed sentences, parsing them to identify relevant entities, and calculating relevancy metrics to construct comprehensive paragraphs that address user concerns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional search indexes are used to provide replies, then the system is simple and fast, but the answers are not comprehensive and fail to address multiple user utterances
Solution Approach 1:
The patent segments the answer generation process into distinct components: syntactic parsing of seed sentences, generation of parse trees, extraction of relevant entities, computation of relevancy metrics, and construction of comprehensive paragraphs. This segmentation allows the system to handle complexity in a structured manner while achieving comprehensive answers that address multiple user utterances.
Solution Approach 2:
The patent performs preliminary actions by pre-parsing seed sentences into syntactic parse trees and pre-identifying relevant entities before actual query processing. This preliminary preparation enables the system to quickly retrieve and combine relevant information when generating comprehensive answers, reducing response time despite the increased complexity.
2Reliability
If comprehensive paragraphs are constructed to address multiple user queries, then the responsiveness and comprehensiveness improve, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary parsing of seed sentences into syntactic parse trees and pre-identification of relevant entities before actual query processing. This preliminary preparation enables the system to quickly retrieve and combine relevant information when generating comprehensive answers, reducing response time despite the increased complexity.
Solution Approach 2:
The patent replaces traditional keyword-based search mechanisms with syntactic parse tree-based matching. By using computational linguistics approaches to analyze sentence structure and compute relevancy metrics based on parse tree similarities, the system achieves more accurate and comprehensive answer generation while optimizing processing efficiency.
Data Source
AI summary
Techniques are described herein for enabling autonomous agents to generate conclusive answers. An example of a conclusive answer is text that addresses concerns of a user who is interacting with an autonomous agent. For example, an autonomous agent interacts with a user device, answering user utterances, for example questions or concerns. Based on the interactions, the autonomous agent determines that a conclusive answer is appropriate. The autonomous agent formulates the conclusive answer, which addresses multiple user utterances. The conclusive answer provided to the user device.