Omni-platform Question Answering System NLP Automation
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Solution Overview
Problem
Current cloud-based database systems face inefficiencies in processing and responding to user-submitted questions across multiple communication platforms, as they often require administrative or expert users to manually check various platforms, leading to increased complexity and delayed responses.
Innovation Solution
An omni-platform question answering system utilizing a multi-layer approach with natural language processing (NLP) to process user queries, generate search queries, rank documents, and merge responses across different types, enabling efficient and accurate question answering across various communication platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If administrative or expert users manually check multiple communication platforms to answer user questions, then accurate responses can be provided, but the system complexity increases and response time delays
Solution Approach 1:
The patent introduces an intermediary question answering system that acts as a mediator between users and administrative/expert users. This system automatically retrieves questions from multiple communication platforms, processes them through NLP and machine learning models, and generates candidate answers without requiring administrative users to manually check each platform. The intermediary system handles the complexity of multi-platform monitoring while maintaining answer accuracy through automated processing and expert validation when needed.
Solution Approach 2:
The system enables self-service by allowing users to submit questions in plain language through any communication platform and receive automated candidate answers generated by the system. The NLP processing, document retrieval, and answer generation occur automatically without requiring administrative user intervention for every question. This reduces system complexity by automating routine operations while maintaining accuracy through the multi-layer processing approach.
2Measurement precision
If administrative or expert users manually check multiple communication platforms to answer user questions, then accurate responses can be provided, but response time is delayed
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and retrieving questions from multiple communication platforms automatically, processing them through NLP and machine learning models to generate candidate answers before administrative users need to review them. The system pre-processes questions, retrieves relevant documents, and prepares answer candidates in advance, significantly reducing the time administrative users need to spend on each question while maintaining accuracy through the structured processing pipeline.
Solution Approach 2:
The system ensures continuous operation by automatically and continuously retrieving questions from multiple communication platforms, processing them through the NLP pipeline, and generating candidate answers without interruption. This continuous automated processing eliminates the delays associated with manual checking of platforms, as the system operates continuously to capture and respond to user questions across all platforms in real-time or near-real-time.
3Adaptability or versatility
If separate configurations are used for each communication platform to receive questions, then platform-specific requirements are met, but the system complexity increases
Solution Approach 1:
The patent implements a universal question answering system that can handle multiple communication platforms through a single unified configuration. The system uses a common NLP processing pipeline, document retrieval mechanism, and answer generation approach that works across email, chat, forum, and other platforms. This multi-functional design allows the system to adapt to different platforms without requiring separate configurations for each, reducing complexity while maintaining platform compatibility through standardized processing interfaces.
Data Source
AI summary
Methods, systems, and devices for processing and answering a natural language query at a database server are described. An end user may submit a question in natural language over a communication platform. An answer engine running on the database server may receive the question, and may process the content of the question using natural language processing (NLP) techniques. The answer engine may construct a search query based on the NLP, and may retrieve a set of documents from a database using the search query. The answer engine may rank the documents, prune the number of documents, modify the documents for the given communication platform, or perform any combination of these functions. In some cases, an intermediate user may review the documents, and may select one or more documents for publication. The answer engine may send the selected documents to the end user as answers in response to the question.