US Patent Application 18245979. INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM simplified abstract
Contents
INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM
Organization Name
Inventor(s)
TAKASHI Yamashita of KANAGAWA (JP)
INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18245979 titled 'INFORMATION PROCESSING DEVICE, INFORMATION PROCESSING METHOD, AND PROGRAM
Simplified Explanation
- The patent application describes an information processing device that can accurately predict an action that a subject may take in a specific situation. - The device includes a prediction unit that uses preference record data, which is a record of the subject's past preference actions related to a specific task, to generate preference prediction data. - The prediction unit inputs the preference record data into a classifier generated by manifold learning, which is a technique used for dimensionality reduction and data visualization. - The prediction unit then applies a prediction model based on assumed information about the specific situation to each classified unit, and outputs the preference prediction data. - The innovation aims to provide high accuracy in predicting a subject's preference action in a given situation, potentially improving decision-making processes or personalization of services.
Original Abstract Submitted
An action that is possible to be executed by a subject in a predetermined situation is predicted with high accuracy. There is provided an information processing device including a prediction unit that outputs preference prediction data indicating prediction of a preference action that is possible to be executed by a subject in a predetermined situation on the basis of preference record data indicating a record of the preference action related to a predetermined task executed by the subject, in which the prediction unit inputs the preference record data to a classifier generated by manifold learning, and outputs the preference prediction data on the basis of applying a prediction model based on assumed information related to the predetermined situation for each of a plurality of classified units.
