Nec corporation (20240119094). DATA CLASSIFICATION DEVICE, DATA CLASSIFICATION METHOD, AND PROGRAM RECORDING MEDIUM simplified abstract
Contents
- 1 DATA CLASSIFICATION DEVICE, DATA CLASSIFICATION METHOD, AND PROGRAM RECORDING MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DATA CLASSIFICATION DEVICE, DATA CLASSIFICATION METHOD, AND PROGRAM RECORDING MEDIUM - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does this technology handle real-time data classification?
- 1.11 What types of classification models are compatible with this device?
- 1.12 Original Abstract Submitted
DATA CLASSIFICATION DEVICE, DATA CLASSIFICATION METHOD, AND PROGRAM RECORDING MEDIUM
Organization Name
Inventor(s)
DATA CLASSIFICATION DEVICE, DATA CLASSIFICATION METHOD, AND PROGRAM RECORDING MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240119094 titled 'DATA CLASSIFICATION DEVICE, DATA CLASSIFICATION METHOD, AND PROGRAM RECORDING MEDIUM
Simplified Explanation
The data classification device described in the abstract includes an acquisition unit, a data classification unit, an output unit, and an input unit. The acquisition unit gathers data to be classified as input data. The data classification unit utilizes a classification model to determine the classification of the input data. The output unit presents display data showing an image divided into multiple groups based on a group division standard determined by the confidence level when the classification model estimates the classification of the input data. Additionally, the output unit displays an image for modifying the group division standard based on input data acquired by the input unit. The classified data is then divided into the multiple groups based on the group division standard indicated by the input result.
- Acquisition unit gathers data to be classified
- Data classification unit uses a classification model to estimate classification
- Output unit displays image divided into groups based on confidence level
- Input unit acquires data for changing group division standard
- Display data shows classified data divided into groups based on input result
Potential Applications
This technology can be applied in various fields such as image recognition, data analysis, and pattern recognition.
Problems Solved
This technology helps in efficiently classifying and organizing large amounts of data, improving decision-making processes, and enhancing data visualization.
Benefits
The benefits of this technology include increased accuracy in data classification, improved data organization, and enhanced visualization of classified data.
Potential Commercial Applications
One potential commercial application of this technology could be in the development of advanced data analysis software for businesses.
Possible Prior Art
Prior art in the field of data classification and visualization technologies may include similar devices or methods used in data processing and analysis software.
Unanswered Questions
How does this technology handle real-time data classification?
The abstract does not specify whether the device can handle real-time data classification or if there are any limitations in processing speed.
What types of classification models are compatible with this device?
The abstract does not mention the specific types of classification models that can be used with this device or if it is limited to certain algorithms.
Original Abstract Submitted
this data classification device comprises an acquisition unit, a data classification unit, an output unit, and an input unit. the acquisition unit acquires data to be classified as input data. the data classification unit uses a classification model to estimate the classification of the input data. the output unit outputs display data displaying: an image divided into a plurality of groups based on a group division standard based on the confidence level when the classification model estimates the classification of the input data; and an image for changing the group division standard. the input unit acquires the data for changing the group division standard as an input result. moreover, the output unit outputs display data in which the classified data is divided into the plurality of groups based on the group division standard indicated by the input result.
