View source for 18272959. INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND COMPUTER PROGRAM simplified abstract (NEC Corporation)

=INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND COMPUTER PROGRAM=


==Organization Name==

[[:Category:NEC Corporation|NEC Corporation]]


[[Category:NEC Corporation]]

==Inventor(s)==

[[:Category:Taiki Miyagawa of Tokyo (JP)|Taiki Miyagawa of Tokyo (JP)]][[Category:Taiki Miyagawa of Tokyo (JP)]]

[[:Category:Akinori Ebihara of Tokyo (JP)|Akinori Ebihara of Tokyo (JP)]][[Category:Akinori Ebihara of Tokyo (JP)]]

==INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND COMPUTER PROGRAM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18272959 titled 'INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND COMPUTER PROGRAM

==Simplified Explanation==

The abstract describes an information processing system that includes an acquisition unit, a calculation unit, a classification unit, and a learning unit. The system is designed to properly select the class to which series data belong from a plurality of classification candidates.

* Acquisition unit obtains a plurality of elements included in series data
* Calculation unit calculates a likelihood ratio based on at least two consecutive elements of the acquired elements
* Classification unit classifies the series data into at least one class of classification candidates based on the likelihood ratio
* Learning unit performs learning related to the calculation of the likelihood ratio using a loss function of a log-sum-exp type

== Potential Applications ==
This technology could be applied in various fields such as:
* Pattern recognition
* Anomaly detection
* Predictive modeling

== Problems Solved ==
This technology helps in:
* Efficient classification of series data
* Improving accuracy in selecting the correct class for the data

== Benefits ==
The benefits of this technology include:
* Enhanced decision-making process
* Increased automation in data classification tasks
* Improved overall system performance

== Potential Commercial Applications ==
Optimizing this technology for commercial use could lead to applications in:
* Financial forecasting
* Medical diagnosis
* Fraud detection

=== Unanswered Questions ===

=== How does this technology handle noisy data in the series? ===

=== What are the computational requirements for implementing this system on a large scale? ===


==Original Abstract Submitted==

An information processing system includes: an acquisition unit that obtains a plurality of elements included in series data; a calculation unit that calculates a likelihood ratio indicating a likelihood of a class to which the series data belong, on the basis of at least two consecutive elements of the plurality of elements; a classification unit that classifies the series data into at least one class of a plurality of classes that are classification candidates, on the basis of the likelihood ratio; and a learning unit that performs learning related to calculation of the likelihood ratio, by using a loss function of a log-sum-exp type. According to such an information processing system, it is possible to properly select the class to which the series data belong, from a plurality of classes that are classification candidates.



[[Category:G06F16/28]]
[[Category:G06F17/18]]