Material Recommendation Apparatus for Automated Substance Selection
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Solution Overview
Problem
Existing systems fail to efficiently identify suitable new materials for industrial products from extensive text-based information due to varying properties required and the difficulty in determining maturity for practical use, necessitating extensive human expertise and time.
Innovation Solution
A material recommendation apparatus comprising an extractor, creator, matcher, and recommender that extracts information from electronic documents, creates time series data associating properties with report times, matches this data with predefined patterns to recommend mature substances for industrial use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If experts manually extract information from extensive academic papers and conference papers, then accurate material identification is achieved, but enormous time and human resources are required
Solution Approach 1:
The patent replaces the manual mechanical process of expert information extraction with an automated computer-based system. The system uses natural language processing and information extraction technologies to automatically parse academic papers and conference papers, identifying material properties and characteristics without human intervention, thereby eliminating the time-consuming manual review process while maintaining identification accuracy
Solution Approach 2:
The patent introduces an intermediary computational system that acts as a bridge between the vast corpus of academic literature and the material selection process. This intermediary system automatically extracts, structures, and analyzes information from papers, transforming unstructured text into structured data that can be efficiently queried and evaluated for material candidate identification
2Loss of information
If experts dedicate enormous time to comprehensive information extraction, then necessary material information is obtained, but productivity remains low
Solution Approach 1:
The patent implements continuous automated information extraction and analysis operations. The system continuously monitors and processes new academic papers and conference papers as they become available, maintaining an up-to-date database of material information without interruption. This continuous operation enables both complete information capture and high productivity by processing multiple papers simultaneously and continuously updating material candidate recommendations
Solution Approach 2:
The patent performs preliminary automated extraction and structuring of material information from papers in advance of actual material selection needs. By pre-processing and organizing material data from the literature before it is needed for specific applications, the system prepares searchable databases and pre-identifies potential material candidates, thereby accelerating the overall material discovery process when specific material needs arise
3Reliability
If comprehensive properties are considered for material selection, then suitable materials are identified, but the complexity of analysis increases
Solution Approach 1:
The patent segments the complex material analysis process into distinct modular components: information extraction from papers, property identification and classification, material candidate evaluation, and recommendation generation. Each module handles specific aspects of the analysis independently, allowing comprehensive property consideration to be broken down into manageable tasks that can be processed systematically without overwhelming complexity
Solution Approach 2:
The patent dynamically adjusts analysis parameters and criteria based on the specific material application and available data. The system can modify which properties are prioritized, what thresholds are applied, and how extensively each property is analyzed depending on the particular material selection context. This parameter adaptability allows comprehensive analysis when needed while simplifying the process when fewer properties are critical, thereby managing analysis complexity flexibly
Data Source
AI summary
According to an embodiment, a material recommendation apparatus includes an extractor, a creator, a matcher and a recommender. The extractor extracts information about a substance as a candidate for a material for an industrial product, a property of the substance, and a report time of the property from an electronic document. The creator creates, for each substance, time series data in which the property is associated with the report time. The matcher matches the time series data with a pattern. The recommender recommends, as the material, a substance corresponding to time series data that matches the pattern.