Knowledge Acquisition Engine for Multi-Source Retrieval
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Solution Overview
Problem
Users face difficulties in obtaining comprehensive information from multiple sources due to the vast amount of data available on the World Wide Web and other information sources, requiring multiple searches and access to various knowledge bases.
Innovation Solution
A method is provided to acquire knowledge from multiple knowledge bases within a knowledge repository by analyzing a search request, generating instructions for sequential requests to be sent to identified knowledge bases, ensuring that the second request includes knowledge from the first base, thereby allowing a single request to retrieve information from multiple sources efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users execute multiple searches to obtain comprehensive information from multiple knowledge bases, then the completeness of information retrieval is improved, but the time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary analysis of the initial search request to identify all relevant knowledge bases that should be queried. It pre-generates a sequence of search requests and prepares the query plan before actual information retrieval begins, allowing multiple knowledge bases to be accessed systematically in a single coordinated operation rather than requiring users to manually execute multiple separate searches
Solution Approach 2:
The system merges multiple separate search operations into a single integrated information retrieval process. By combining the identification of multiple knowledge bases, generation of sequential requests, and coordinated querying into one unified system operation, it achieves comprehensive information retrieval without requiring users to perform multiple independent search actions
2Loss of information
If users access multiple knowledge bases manually to retrieve comprehensive information, then the completeness of information retrieval is improved, but the ease of operation deteriorates
Solution Approach 1:
The system performs self-service by automatically analyzing the initial search request, identifying relevant knowledge bases, generating the sequence of required search requests, and executing the queries without user intervention. The system autonomously manages the entire multi-knowledge base retrieval process, freeing users from the burden of manually coordinating multiple searches across different knowledge bases
Solution Approach 2:
The system acts as an intermediary between the user's initial search request and the multiple knowledge bases. It receives the user's single search request, automatically determines which knowledge bases are relevant, generates the appropriate sequence of queries, and retrieves information from multiple sources, presenting comprehensive results to the user without requiring them to directly interact with multiple knowledge bases
3Ease of operation
If a single search request is used to retrieve information, then the ease of operation is improved, but the completeness of information retrieval deteriorates
Solution Approach 1:
The system performs preliminary analysis of the single search request to identify all relevant knowledge bases that should be queried. It pre-generates a sequence of search requests and prepares the query plan before actual information retrieval begins, allowing comprehensive information to be retrieved from multiple knowledge bases through what appears to be a single user action
Solution Approach 2:
The system provides multi-functionality by enabling a single search request to access multiple different knowledge bases. It universally handles the task of identifying relevant knowledge bases, generating appropriate queries for each, and retrieving comprehensive information across diverse sources, making the single search request as effective as multiple manual searches
Data Source
AI summary
One implementation provides a method for acquiring knowledge from multiple knowledge bases in a knowledge repository. The method includes identifying first and second knowledge bases within the knowledge repository by analyzing a search request received from a client system. The first knowledge base contains knowledge of a first type and the second knowledge base contains knowledge of a second type. The method further includes generating instructions that, when executed, cause first and second requests to be sent to the knowledge repository in sequential fashion to acquire knowledge from the first and second knowledge bases, such that the second request is sent after the first request, and such that the second request includes knowledge of the first type from the first knowledge base acquired in response to the first request.