Knowledge Bot Query Routing for Multi-Domain Search
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Solution Overview
Problem
Existing service platforms require users to navigate manually to find desired data and services, which can be cumbersome and inefficient, especially when the desired information is not pre-defined, and updating these platforms is burdensome for service providers.
Innovation Solution
A knowledge bot system that dynamically searches across multiple domains using inverted and vector indices, integrates with machine learning models, and employs a semantic cache layer to provide intuitive and flexible responses to user queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a knowledge bot system with dynamic multi-domain search is implemented, then information accessibility and response quality are improved, but device complexity and computational resource requirements increase
Solution Approach 1:
The system segments information retrieval into multiple specialized search engines (keyword-based, semantic, hybrid) that operate independently but coordinate through a unified framework. Each search engine handles specific types of queries, dividing the complex task of information retrieval into manageable components that can be selected and executed based on query characteristics.
Solution Approach 2:
The patent introduces intermediary components including a query router that directs user queries to appropriate search engines, and a response synthesizer that aggregates results from multiple search engines. These intermediaries manage the complexity by providing a standardized interface between the user and the complex multi-engine search system, hiding the underlying complexity while maintaining high information accessibility.
2Measurement precision
If multiple search engines are integrated for comprehensive search, then search coverage and accuracy are improved, but computational resources and processing time increase
Solution Approach 1:
The system dynamically selects and configures search engines based on the characteristics of each user query. The query router analyzes the query and determines which search engine(s) are most appropriate, allowing the system to use only the necessary computational resources for each specific search task rather than always activating all search engines. This dynamic adaptation optimizes the balance between search accuracy and computational resource consumption.
Solution Approach 2:
The patent employs parameter changes by adjusting search thresholds, result quantities, and engine selection criteria based on query importance, user preferences, and system load conditions. This allows the system to maintain high search accuracy when needed while reducing computational resources during routine queries or high-load periods, achieving flexibility in resource allocation.
3Ease of manufacture
If pre-generated FAQ pages are used for user assistance, then ease of implementation is improved, but adaptability to new information and user needs deteriorates
Solution Approach 1:
The knowledge bot system provides self-service capabilities by automatically retrieving, processing, and responding to user queries using multiple search engines. Unlike static FAQ pages that require manual updates, the system autonomously adapts to new information by searching updated knowledge bases and documents, automatically incorporating new content without requiring service provider intervention for each update.
Solution Approach 2:
The system performs preliminary actions by pre-processing and indexing large volumes of documentation and knowledge base content before users need information. This preliminary indexing enables rapid retrieval and adaptation when users submit queries, allowing the system to quickly respond to new information needs without requiring manual reconfiguration of the assistance system.
4Stability of the object's composition
If manual navigation through platforms is required, then platform structure stability is improved, but user time and operational efficiency deteriorate
Solution Approach 1:
The knowledge bot acts as an intermediary between users and the platform's information architecture. Instead of requiring users to manually navigate through the platform's structured pages and menus, the bot intermediates by understanding user intent, querying multiple search engines, and presenting relevant information directly. This preserves the stability of the underlying platform structure while eliminating the time loss associated with manual navigation.
Data Source
AI summary
Methods and systems are presented for providing a knowledge bot configurable to interact with users across multiple domains. The knowledge bot includes at least a text-based search engine and a semantic-based search engine. Each of the search engine is configured to retrieve documents from a corpus of documents based on the user query. The user query is in a natural language format. The retrieved documents may be ranked according to how relevant the documents are to the user query. A subset of the documents is used as the search results based on the ranking. The search results from the search engine are combined with the user query to generate a prompt for an artificial intelligence model. Based on the prompt, a response in the natural language format is generated by the artificial intelligence model.