18276378. CLASSIFICATION SYSTEM, METHOD, AND PROGRAM simplified abstract (NEC Corporation)

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 18276378 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 inputs of test data and classification scores
• Calculates classification scores for unseen classes based on uniformity
• Determines matching scores for similarity between test data and class labels
• Calculates final classification scores based on classification and matching scores

Potential Applications

This technology could be applied in various fields such as:

• Image recognition
• Speech recognition
• Fraud detection
• Medical diagnosis

Problems Solved

This technology helps in:

• Improving accuracy in classification tasks
• Handling unseen classes efficiently
• Enhancing decision-making processes

Benefits

The benefits of this technology include:

• Increased accuracy in classification
• Improved performance in handling unseen classes
• Enhanced decision-making capabilities

Potential Commercial Applications

This technology could be utilized in:

• E-commerce for product recommendations
• Healthcare for disease diagnosis
• Finance for fraud detection
• Marketing for customer segmentation

Possible Prior Art

One possible prior art for this technology could be the use of machine learning algorithms for classification tasks in various industries.

What is the impact of this technology on the accuracy of classification tasks?

This technology significantly improves the accuracy of classification tasks by calculating final classification scores based on classification and matching scores, leading to more precise results.

How does this technology handle unseen classes efficiently?

This technology efficiently handles unseen classes by calculating classification scores for unseen classes based on the uniformity of the classification scores of each seen class, ensuring a balanced approach to classification.

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.