Nec corporation (20240119079). CLASSIFICATION SYSTEM, METHOD, AND PROGRAM simplified abstract

CLASSIFICATION SYSTEM, METHOD, AND PROGRAM

Organization Name

nec corporation

Inventor(s)

Taro Yano of Tokyo (JP)

Kunihiro Takeoka of Tokyo (JP)

Masafumi Oyamada of Tokyo (JP)

CLASSIFICATION SYSTEM, METHOD, AND PROGRAM - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240119079 titled 'CLASSIFICATION SYSTEM, METHOD, AND PROGRAM

Simplified Explanation

The input means accepts inputs of test data, a hierarchical structure in which a node of bottom layer represents a target class, and a classification score of a seen class as the classification score indicating a probability that the test data is classified into each class. The unseen class score calculation means calculates the classification score of an unseen class based on uniformity of the classification score of each seen class. The matching score calculation means calculates a matching score indicating similarity between the test data and each class label. The final classification score calculation means calculates a final classification score indicating a probability that the test data is classified into the class so that the larger the classification score of each class, and the matching score, the larger the final classification score.

• Accepts test data inputs
• Hierarchical structure with target class nodes
• Calculates classification scores for seen and unseen classes
• Determines matching score for similarity
• Computes final classification score based on class scores and matching score

Potential Applications

This technology can be applied in various fields such as image recognition, natural language processing, and pattern recognition.

Problems Solved

This technology helps in accurately classifying test data into different classes based on classification scores and matching scores.

Benefits

The benefits of this technology include improved accuracy in classification tasks, better decision-making processes, and enhanced performance in various applications.

Potential Commercial Applications

One potential commercial application of this technology is in the development of advanced machine learning models for industries such as healthcare, finance, and e-commerce.

Possible Prior Art

Prior art in this field may include existing classification algorithms, machine learning models, and pattern recognition techniques.

How does this technology handle noisy or incomplete data in the test inputs?

This technology does not address how it handles noisy or incomplete data in the test inputs. Additional research may be needed to understand its robustness in such scenarios.

Can this technology be easily integrated with existing machine learning frameworks and tools?

The article does not provide information on the compatibility of this technology with existing machine learning frameworks and tools. Further investigation is required to determine the ease of integration.

Original Abstract Submitted

the input means accepts inputs of test data, a hierarchical structure in which a node of bottom layer represents a target class, and a classification score of a seen class as the classification score indicating a probability that the test data is classified into each class. the unseen class score calculation means calculates the classification score of an unseen class based on uniformity of the classification score of each seen class. the matching score calculation means calculates a matching score indicating similarity between the test data and each class label. the final classification score calculation means calculates a final classification score indicating a probability that the test data is classified into the class so that the larger the classification score of each class, and the matching score, the larger the final classification score.