18357234. DATA PROCESSING DEVICE, STORAGE MEDIUM, AND DATA PROCESSING METHOD simplified abstract (Fujitsu Limited)
Contents
- 1 DATA PROCESSING DEVICE, STORAGE MEDIUM, AND DATA PROCESSING METHOD
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DATA PROCESSING DEVICE, STORAGE MEDIUM, AND DATA PROCESSING METHOD - 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
DATA PROCESSING DEVICE, STORAGE MEDIUM, AND DATA PROCESSING METHOD
Organization Name
Inventor(s)
Makiko Konoshima of Kawasaki (JP)
Hirotaka Tamura of Yokohama (JP)
DATA PROCESSING DEVICE, STORAGE MEDIUM, AND DATA PROCESSING METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 18357234 titled 'DATA PROCESSING DEVICE, STORAGE MEDIUM, AND DATA PROCESSING METHOD
Simplified Explanation
The data processing device described in the patent application is designed to detect the magnitude of correlation between a pair of continuous variables within a set of continuous variables. It achieves this by utilizing information from a first evaluation function obtained through formulating a combinatorial optimization problem. The device then allocates a larger number of common binary variables to the continuous variable pair based on the strength of the correlation. It generates correspondence information to indicate the relationship between each continuous variable and the binary variable, converts the first evaluation function into a second evaluation function of Ising-type that includes binary variables, sets coefficient information for the second evaluation function, and searches for a solution to the optimization problem using the second evaluation function and coefficient information.
- Detect magnitude of correlation between continuous variable pair
- Allocate more binary variables to pair based on correlation strength
- Generate correspondence information between continuous and binary variables
- Convert first evaluation function to Ising-type second evaluation function
- Set coefficient information for second evaluation function
- Search for solution to optimization problem using second evaluation function and coefficients
Potential Applications
This technology could be applied in various fields such as finance, healthcare, and marketing for analyzing complex data sets and identifying patterns or relationships between variables.
Problems Solved
This technology helps in efficiently detecting and quantifying correlations between continuous variables, which can be challenging in large datasets with numerous variables.
Benefits
- Improved accuracy in identifying correlations - Enhanced efficiency in data analysis - Potential for discovering hidden patterns or relationships in data
Potential Commercial Applications
Optimizing resource allocation, risk assessment in financial markets, personalized medicine based on patient data analysis.
Possible Prior Art
One possible prior art could be the use of machine learning algorithms to detect correlations between variables in data sets. Another could be the application of combinatorial optimization techniques in data analysis.
Unanswered Questions
How does this technology compare to existing methods for detecting correlations in data sets?
This article does not provide a direct comparison to existing methods for detecting correlations in data sets. It would be helpful to know the advantages and limitations of this technology compared to traditional statistical methods or machine learning algorithms.
What are the potential limitations or challenges in implementing this technology in real-world applications?
The article does not address the potential limitations or challenges in implementing this technology in real-world applications. It would be important to understand factors such as computational complexity, data requirements, and scalability issues that may arise when using this technology in practical scenarios.
Original Abstract Submitted
A data processing device configured to: detect magnitude of correlate on of a continuous variable pair included in a plurality of continuous variables based on information regarding a first evaluation function that includes the plurality of continuous variables obtained by formulating a combinatorial optimization problem, allocate a larger number of common binary variables to the continuous variable pair as the correlation is larger at a time of allocating a binary variable to each of the plurality of continuous variables, generate correspondence information that indicates a correspondence relationship between each of the plurality of continuous variables and the binary variable, convert the first evaluation function into a second evaluation function that includes a plurality of binary variables, the second evaluation function being Ising-type, set coefficient information of the second evaluation function, and search for a solution to the combinatorial optimization problem using the second evaluation function and the coefficient information.
