18255034. PROCESSING SYSTEM, LEARNING PROCESSING SYSTEM, PROCESSING METHOD, AND PROGRAM simplified abstract (Panasonic Intellectual Property Management Co., Ltd.)
PROCESSING SYSTEM, LEARNING PROCESSING SYSTEM, PROCESSING METHOD, AND PROGRAM
Organization Name
Panasonic Intellectual Property Management Co., Ltd.
Inventor(s)
Jeffry Nainggolan of Osaka (JP)
PROCESSING SYSTEM, LEARNING PROCESSING SYSTEM, PROCESSING METHOD, AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18255034 titled 'PROCESSING SYSTEM, LEARNING PROCESSING SYSTEM, PROCESSING METHOD, AND PROGRAM
Simplified Explanation
The processing system described in the abstract includes multiple components such as acquirers, an identifier, and an extractor, all working together to identify and extract relevant data based on a learned model.
- The first acquirer gathers learning data with assigned labels.
- The second acquirer obtains a learned model created from the learning data.
- The third acquirer collects identification data with labels.
- The identifier identifies the identification data using the learned model.
- The extractor extracts similar pieces of learning data based on the identified data and the learned model.
- Potential Applications:**
- Data mining
- Pattern recognition
- Image recognition
- Fraud detection
- Problems Solved:**
- Efficient data identification
- Accurate data extraction
- Improved data analysis
- Benefits:**
- Enhanced data processing
- Increased accuracy in data matching
- Streamlined data retrieval
Original Abstract Submitted
A processing system includes a first acquirer, a second acquirer, a third acquirer, an identifier, and an extractor. The first acquirer is configured to acquire a plurality of pieces of learning data to which labels have been assigned. The second acquirer is configured to acquire a learned model generated based on the plurality of pieces of learning data. The third acquirer is configured to acquire identification data to which a label has been assigned. The identifier is configured to identify the identification data on a basis of the learned model. The extractor is configured to extract, based on an index which is applied in the learned model and which relates to similarity between the identification data and each of the plurality of pieces of learning data, one or more pieces of learning data similar to the identification data from the plurality of pieces of learning data.
