View source for 18276385. ORDER PREDICTION DEVICE, ORDER PREDICTION METHOD, LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM simplified abstract (NEC Corporation)

=ORDER PREDICTION DEVICE, ORDER PREDICTION METHOD, LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM=


==Organization Name==

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


[[Category:NEC Corporation]]

==Inventor(s)==

[[:Category:Shizuka Sato of Tokyo (JP)|Shizuka Sato of Tokyo (JP)]][[Category:Shizuka Sato of Tokyo (JP)]]

[[:Category:Shohei Maruyama of Tokyo (JP)|Shohei Maruyama of Tokyo (JP)]][[Category:Shohei Maruyama of Tokyo (JP)]]

==ORDER PREDICTION DEVICE, ORDER PREDICTION METHOD, LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18276385 titled 'ORDER PREDICTION DEVICE, ORDER PREDICTION METHOD, LEARNING DEVICE, LEARNING METHOD, AND RECORDING MEDIUM

==Simplified Explanation==

The patent application describes a device that predicts the order of events based on event data using an attention mechanism.

* Acquisition means gathers event data related to an event.
* Prediction means forecasts the level of interest for each data item in the event data and predicts the order using an attention mechanism.
* Output means provides the prediction result including the degree of interest and order probability.

== Potential Applications ==
This technology could be applied in various fields such as personalized recommendations, content curation, and event scheduling.

== Problems Solved ==
This technology helps in predicting the order of events accurately, which can improve user experience, increase engagement, and optimize resource allocation.

== Benefits ==
The device can enhance decision-making processes, increase efficiency, and provide personalized experiences for users.

== Potential Commercial Applications ==
One potential commercial application of this technology could be in the entertainment industry for recommending movies or TV shows based on user preferences.

== Possible Prior Art ==
One possible prior art for this technology could be recommendation systems used in e-commerce platforms to suggest products to customers based on their browsing history and preferences.

=== Unanswered Questions ===

=== How does the attention mechanism work in predicting the order of events? ===
The attention mechanism in the device focuses on different parts of the event data to predict the order accurately.

=== What are the specific algorithms used in predicting the degree of interest for each data item? ===
The specific algorithms used in predicting the degree of interest for each data item are not mentioned in the abstract.


==Original Abstract Submitted==

In an order prediction device, an acquisition means acquires event data related to an event. A prediction means predicts a degree of interest with respect to each data item included in the event data and an order prediction by using an attention mechanism based on the event data. An output means outputs, as a prediction result, the degree of interest and an order probability.



[[Category:G06N5/022]]