18333949. METHOD AND INFORMATION PROCESSING DEVICE simplified abstract (Kioxia Corporation)
Contents
- 1 METHOD AND INFORMATION PROCESSING DEVICE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND INFORMATION PROCESSING DEVICE - 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
METHOD AND INFORMATION PROCESSING DEVICE
Organization Name
Inventor(s)
Daisuke Miyashita of Kawasaki (JP)
METHOD AND INFORMATION PROCESSING DEVICE - A simplified explanation of the abstract
This abstract first appeared for US patent application 18333949 titled 'METHOD AND INFORMATION PROCESSING DEVICE
Simplified Explanation
The method described in the abstract involves using a neural network model to select objects based on a query, calculating distances between data associated with the selected object and the query, and identifying the closest data to the query.
- The method involves receiving a query and selecting objects based on a neural network model.
- Each selected object is associated with data stored in memory.
- Distances between the query and data associated with the selected object are calculated.
- The closest data to the query is identified based on the calculated distances.
Potential Applications
This technology could be applied in various fields such as recommendation systems, information retrieval, and data analysis.
Problems Solved
This technology helps in efficiently retrieving relevant data based on a query, improving the accuracy and speed of information retrieval systems.
Benefits
The method allows for more accurate and efficient data retrieval, leading to better decision-making and improved user experience.
Potential Commercial Applications
This technology could be utilized in e-commerce platforms for personalized recommendations, search engines for improved results, and data analysis tools for faster insights.
Possible Prior Art
One possible prior art could be traditional recommendation systems that use collaborative filtering or content-based filtering techniques for data retrieval.
What are the specific neural network models used in this method?
The abstract does not specify the exact neural network models used in the method.
How is the distance metric calculated between the query and the data?
The abstract does not provide details on the specific method used to calculate the distance metric between the query and the data associated with the selected object.
Original Abstract Submitted
According to an embodiment, a method includes receiving a query, and selecting one of first objects on the basis of the query and a neural network model. Each of the first objects is associated with one or more pieces of first data in a group of first data stored on a first memory. The method further includes calculating a metric of a distance between the query and one or more pieces of second data. The one or more pieces of second data are one or more pieces of first data associated with a second object. The second object is the one of the first objects having been selected. The method further includes identifying third data on the basis of the metric of the distance. The third data is first data closest to the query in the group of the first data.
