Expert Knowledge Base Vector Space for Reliable Information Retrieval
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Solution Overview
Problem
Conventional search engines and generative AI chats provide inaccurate, outdated, or misleading information due to the lack of verification of the reliability of webpages indexed by web crawlers, posing challenges for users seeking informed decisions.
Innovation Solution
A computer-implemented method and system that utilizes an expert knowledge base vector space to identify and provide reliable answers by mapping query vectors to expert answer vectors within a threshold distance, ensuring answers are from verified experts, and updating the knowledge base dynamically with expert inputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional search engines and generative AI chats index webpages using web crawlers, then the quantity of information available to users increases, but the reliability and accuracy of the information deteriorates due to lack of verification
Solution Approach 1:
The patent segments the information retrieval system into multiple specialized components: a traditional search engine for broad information coverage, a question answering system for direct answers, and a verification module for credibility assessment. Each component handles specific aspects of information processing, allowing the system to maintain both high information quantity and high reliability through division of labor among specialized subsystems
Solution Approach 2:
The patent introduces an intermediary verification module that acts as a mediator between the information source (webpages) and the user. This verification module assesses the credibility of information sources and the accuracy of content before presenting it to users, thereby resolving the contradiction by adding a filtering layer that maintains information quantity while improving reliability through intermediate verification
2Speed
If search engines provide various webpages as results without verification, then the speed of information retrieval is improved, but the accuracy and truthfulness of information deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-verified and pre-processing information through multiple filters before it reaches the user. The system pre-assesses source credibility, pre- validates content accuracy, and pre-organizes information through a knowledge graph structure, so that when users query, they receive immediately verified accurate information without requiring real-time verification that would slow down retrieval
Solution Approach 2:
The patent implements a dynamic information retrieval system that adapts its verification depth and retrieval speed based on query characteristics and user needs. For high-stakes queries requiring high accuracy, the system performs more thorough verification; for routine queries, it provides faster responses with standard verification, thus dynamically balancing speed and accuracy requirements
3Reliability
If expert knowledge base vector spaces are used to map query vectors to expert answer vectors, then the reliability of answers is improved, but the device complexity increases due to multidimensional vector space operations
Solution Approach 1:
The patent uses copying by creating vector representations (embeddings) of expert knowledge and queries. Instead of directly comparing complex unstructured expert knowledge, the system copies semantic meaning into standardized vector formats that can be efficiently compared using mathematical operations. This copying approach maintains reliability through precise semantic matching while reducing complexity by transforming complex knowledge into manageable vector representations
Solution Approach 2:
The patent replaces manual expert verification mechanisms with automated computational vector space operations. Instead of relying on mechanical processes of human experts reviewing and validating each query, the system substitutes this with automated vector similarity calculations and mathematical operations in the vector space, thereby improving reliability through consistent automated validation while managing complexity through algorithmic efficiency
4Measurement precision
If the system maps query vectors to expert answer vectors within threshold distance, then the precision of answer matching is improved, but the loss of time increases due to comprehensive searching in vector space
Solution Approach 1:
The patent applies partial action by implementing a tiered search strategy that performs partial vector space searches with threshold-based filtering. Instead of exhaustively searching the entire vector space, the system performs partial searches limited to relevant regions identified through initial filtering, using threshold distance calculations to stop searching once sufficient matches are found, thus achieving high precision without the time cost of complete exhaustive search
Data Source
AI summary
The application generally relates providing reliable information to a user. A device may receive a query. A device may identify that the query relates to a field of expertise. A device may perform a search based on the query on an expert knowledge base vector space in the field of expertise. A device may identify at least one expert answer from the expert knowledge base vector space that is responsive to the query. A device may provide a response to the query, wherein the response includes the at least one expert answer.