Unified Self-Help System for Multi-System Content Search
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Solution Overview
Problem
Current customer self-help systems are inefficient due to content duplication and redundancy across multiple data management systems offered by the same provider, leading to increased storage costs and poor search performance, as each system operates independently without an effective method to identify and share relevant content.
Innovation Solution
The use of special data training sets, operational models, and algorithms to probabilistically identify and share potentially common relevant content across multiple customer self-help systems, leveraging AI and machine learning to analyze and filter relevant data in response to user queries, thereby reducing the need to search large volumes of irrelevant content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple customer self-help systems are operated independently for different data management systems, then each system can be maintained as a separate business unit, but content duplication and redundancy occur across systems
Solution Approach 1:
The patent merges multiple independent customer self-help systems into a unified system that serves multiple data management systems. A single self-help system is implemented that can dynamically adapt to serve different data management systems, eliminating the need for separate independent systems and reducing content duplication across systems.
Solution Approach 2:
The self-help system is designed with universal functionality to serve multiple data management systems simultaneously. It implements dynamic configuration capabilities that allow the same system to adapt to different data management systems' requirements, making one system perform multiple functions that previously required separate systems.
2Measurement precision
If all self-help content from multiple systems is searched to ensure comprehensive coverage, then user query accuracy improves, but search performance and processing time deteriorate
Solution Approach 1:
The unified self-help system segments content by associating it with specific data management systems through configuration data. When a user submits a query, the system segments the search space by identifying which data management system the query relates to and only searching relevant content, rather than searching all content from all systems.
Solution Approach 2:
The system performs preliminary classification and organization of self-help content during ingestion, tagging content with associated data management system identifiers. This preliminary action enables efficient filtering and targeted searching later, avoiding the need to scan all content when responding to queries.
3Adaptability or versatility
If separate self-help systems are maintained for each data management system, then system independence is preserved, but storage costs and maintenance complexity increase
Solution Approach 1:
The patent implements a universal self-help system that can serve multiple data management systems through dynamic configuration. The system maintains independence and adaptability to different data management systems while being implemented as a single unified platform, reducing the number of separate systems from multiple to one.
Solution Approach 2:
The self-help system implements dynamic configuration capabilities that allow it to adapt its behavior and content filtering based on which data management system is being accessed. The system can dynamically adjust its parameters, content selection, and response generation to match the specific requirements of different data management systems.
Data Source
AI summary
A customer self-help system employs artificial intelligence and machine learning to identify self-help content that is responsive to a user query by analyzing and searching a plurality of customer self-help systems. The customer self-help system generates a self-help relationship model by applying one or more processes/algorithms on training set data. In response to a user query, the customer self-help system identifies ones of the plurality of customer self-help systems that are relevant to the user query and searches the relevant ones of the plurality of customer self-help systems for self-help content that is responsive to the user query. The customer self-help system then provides the self-help content to the user in response to receipt of the user query from the user.