18546100. INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM simplified abstract (Sony Group Corporation)
Contents
- 1 INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM - 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 Original Abstract Submitted
INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM
Organization Name
Inventor(s)
Takahiro Ishikawa of Tokyo (JP)
INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18546100 titled 'INFORMATION PROCESSING APPARATUS, INFORMATION PROCESSING METHOD, AND PROGRAM
Simplified Explanation
The patent application describes an information processing apparatus that evaluates text based on predetermined evaluation criteria defined by multiple sub-goals. The evaluation section uses supervised learning to input text features related to a comparison target and an evaluation target, then calculates the similarity between the two targets for each sub-goal. The evaluation section further compares the similarity between the evaluation target and comparison target for each sub-goal to an ideal pattern for the predetermined evaluation criteria.
- The evaluation section of the apparatus inputs text features related to a comparison target and an evaluation target.
- The apparatus calculates the similarity between the evaluation target and comparison target for each sub-goal.
- The evaluation section compares the similarity between the evaluation target and comparison target for each sub-goal to an ideal pattern for the predetermined evaluation criteria.
Potential Applications
This technology could be applied in various fields such as natural language processing, sentiment analysis, and recommendation systems.
Problems Solved
This technology helps in automating the evaluation process based on text data, which can be time-consuming and subjective when done manually.
Benefits
The benefits of this technology include improved accuracy and efficiency in evaluating text data, leading to better decision-making and personalized recommendations.
Potential Commercial Applications
One potential commercial application of this technology could be in customer feedback analysis for businesses to understand customer sentiments and improve their products or services.
Possible Prior Art
One possible prior art for this technology could be existing text analysis tools that use machine learning algorithms to evaluate text data.
What are the limitations of this technology in real-world applications?
The limitations of this technology in real-world applications could include the need for large amounts of labeled data for training the classifiers, potential biases in the evaluation criteria, and the complexity of defining and optimizing the sub-goals.
How does this technology compare to existing text analysis tools in terms of accuracy and efficiency?
This technology aims to improve accuracy and efficiency in evaluating text data by considering multiple sub-goals and ideal patterns for evaluation criteria, which could potentially outperform existing text analysis tools in certain applications.
Original Abstract Submitted
An information processing apparatus includes an evaluation section that inputs to a first classifier generated by supervised learning that uses a feature amount extracted from text in which a characteristic of a comparison target evaluated to satisfy a predetermined evaluation criteria defined by a combination of multiple sub goals of the predetermined goal is described, a feature amount extracted from the text in which the characteristic of the evaluation target is described, to acquire a similarity between the evaluation target and the comparison target for each of the sub goals. Further, the evaluation section evaluates, in reference to the similarity between the evaluation target and the comparison target for each of the sub goals and an ideal pattern for each of the predetermined evaluation criteria defined by a combination of the multiple sub goals, the similarity between the ideal pattern for each of the predetermined evaluation criteria and evaluation target.
