Bio-Inspired Retrieval System for Physical and Ecological Relations
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Solution Overview
Problem
Conventional biological knowledge retrieval systems are inadequate for supporting cognitive searches, as they primarily provide limited information on biological relations and lack integrated retrieval of physical and ecological information, restricting the scope of bio-inspired design applications.
Innovation Solution
A biological system information retrieval system that uses a query inputting and parsing unit to generate corpus data sets for current and expected results, assessing similarity based on physical, ecological, and biological relations, and generating network graphs for effective retrieval and design applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional retrieval algorithms are used for biological knowledge, then keyword search capability is provided, but the system cannot support cognitive search process and provides limited information scope
Solution Approach 1:
The patent merges biological relations, physical relations, and ecological relations into a single integrated retrieval system. The system combines multiple types of relational data that were previously separated, allowing simultaneous access to biological, physical, and ecological information through unified search queries, thereby expanding information scope without losing any relation type.
Solution Approach 2:
The retrieval system is designed to handle multiple types of queries and return diverse information types through a single platform. It can retrieve biological relations, physical relations, and ecological relations, and can operate with different search methods (keyword search, image matching, semantic search), making the system universally applicable for various bio-inspired design needs.
2Loss of information
If conventional retrieval systems provide comprehensive information, then information coverage is improved, but the retrieval algorithm remains poor at supporting cognitive search process
Solution Approach 1:
The patent introduces an intermediary layer between the user query and the database that performs semantic analysis and interpretation. This intermediary component translates natural language queries into structured search operations, enabling the system to understand cognitive search intent and provide relevant results across multiple information types without requiring users to master complex search syntax.
Solution Approach 2:
The system replaces traditional mechanical keyword-matching algorithms with semantic analysis mechanisms that understand the meaning and context of queries. This substitution enables the system to support cognitive search processes by interpreting user intent rather than simply matching keywords, thereby improving ease of operation while maintaining comprehensive information coverage.
3Loss of information
If the system integrates multiple types of relations (physical, ecological, biological), then information comprehensiveness is improved, but system complexity increases
Solution Approach 1:
The patent segments the integrated retrieval system into distinct functional modules: a biological relations module, a physical relations module, and an ecological relations module. Each module handles specific types of relations independently, but they are coordinated through a unified query interface. This segmentation allows the system to maintain comprehensive information coverage while managing complexity through modular architecture.
Solution Approach 2:
The system employs a universal retrieval framework that handles multiple types of relations through a single integrated interface. Rather than requiring separate systems for biological, physical, and ecological relations, the multi-functional framework processes all relation types uniformly, reducing overall system complexity while maintaining information comprehensiveness.
4Adaptability or versatility
If the system provides detailed biological system information, then design applicability is improved, but retrieval precision requirements increase
Solution Approach 1:
The patent implements dynamic retrieval precision adjustment based on the type of design application. The system can adapt its precision requirements according to the query context and desired application outcome, allowing detailed biological system information to be retrieved with appropriate precision levels for different design scenarios, thereby improving design applicability without requiring uniformly high precision across all queries.
Data Source
AI summary
Biological system information retrieval system and method thereof disclosed. The biological system information retrieval system may include a query inputting unit, configured for inputting a retrieval query being described to have at least one of a current state and an expected result, a query parsing unit, configured for extracting a token for the current state and the expected result from the retrieval query, and generating at least one of a first corpus data set for the current state and a second corpus data set for the expected result by using the token, and a retrieval requesting unit, configured for inputting at least one of the first corpus data set and the second corpus data set and an option value being generated according to a predetermined syntax to an information management device in order to retrieve a biological system information having similarity.