Nec corporation (20240104433). LEARNING SYSTEM, LEARNING METHOD, AND RECORDING MEDIUM simplified abstract
Contents
- 1 LEARNING SYSTEM, LEARNING METHOD, AND RECORDING MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 LEARNING SYSTEM, LEARNING METHOD, AND 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 compare to existing learning systems that rely on key phrases for accuracy?
- 1.11 What are the potential limitations of this technology in real-world applications?
- 1.12 Original Abstract Submitted
LEARNING SYSTEM, LEARNING METHOD, AND RECORDING MEDIUM
Organization Name
Inventor(s)
Kunihiro Takeoka of Tokyo (JP)
LEARNING SYSTEM, LEARNING METHOD, AND RECORDING MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104433 titled 'LEARNING SYSTEM, LEARNING METHOD, AND RECORDING MEDIUM
Simplified Explanation
The learning system described in the patent application includes an acquisition unit, a generation unit, a restoration unit, and a learning unit. The acquisition unit obtains document data, the generation unit generates a key phrase from the document data, the restoration unit restores the document data from the generated key phrase, and the learning unit learns parameters of the generation unit based on the document data and the restored document data. This system allows for high-precision learning even without a key phrase as a correct answer.
- Acquisition unit obtains document data
- Generation unit generates key phrase from document data
- Restoration unit restores document data from key phrase
- Learning unit learns parameters of generation unit based on document data and restored document data
Potential Applications
The technology described in this patent application could be applied in various fields such as education, content creation, data analysis, and information retrieval systems.
Problems Solved
This technology solves the problem of performing high-precision learning without the need for a key phrase as a correct answer, which can improve the accuracy and efficiency of learning systems.
Benefits
The benefits of this technology include improved learning accuracy, enhanced data restoration capabilities, and increased efficiency in parameter learning processes.
Potential Commercial Applications
A potential commercial application of this technology could be in the development of advanced learning systems for educational institutions, content creation platforms, and data analysis tools.
Possible Prior Art
One possible prior art for this technology could be the use of machine learning algorithms in natural language processing tasks to generate key phrases and restore document data.
Unanswered Questions
How does this technology compare to existing learning systems that rely on key phrases for accuracy?
This article does not provide a direct comparison between this technology and existing learning systems that rely on key phrases for accuracy.
What are the potential limitations of this technology in real-world applications?
This article does not address the potential limitations of this technology in real-world applications, such as scalability, computational resources required, or adaptability to different types of document data.
Original Abstract Submitted
a learning system includes: an acquisition unit that obtains document data; a generation unit that generates a key phrase from the document data; a restoration unit that restores the document data from the generated key phrase; and a learning unit that learns parameters of the generation unit on the basis of the document data and the restored document data. according to such a learning system, high-precision learning can be performed even when there is no key phrase as a correct answer.
