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1.发明公开公开(公告)号：US20240193920A1
公开(公告)日：2024-06-13
申请号：US18536536
申请日：2023-12-12
Applicant: Korea Electronics Technology Institute
Inventor： Jae Woong YOO , Mi Ra LEE , Hye Dong JUNG
CPC classification number: G06V10/7715 , G06V10/44 , G06V10/764 , G06V10/806 , G06V40/20 , G10L15/02 , G10L15/08
Abstract: There is provided a method for predicting a user personality by mapping multimodal information on a personality expression space. A personality prediction method according to an embodiment extracts a multimodal feature from an input image in which a user appears, maps the extracted multimodal feature on a personality expression space, and predicts a personality of the user based on a result of mapping. Accordingly, a personality of a user may be more exactly predicted through establishment of a correlation between user's various behavior characteristics and personalities.
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2.发明公开公开(公告)号：US20240193969A1
公开(公告)日：2024-06-13
申请号：US18536856
申请日：2023-12-12
Applicant: Korea Electronics Technology Institute
Inventor： Jae Woong YOO , Mi Ra LEE , Hye Dong JUNG
CPC classification number: G06V20/70 , G06V10/44 , G06V10/761
Abstract: There is provided a method for creating multimodal training datasets for predicting characteristics of a user by using pseudo-labeling. According to an embodiment, the method may acquire a labelled dataset in which an image of a user is labelled with personality information and may extract a multimodal feature vector from the image of the acquired labelled dataset, may acquire an un-labelled dataset in which an image of a user is not labelled with personality information and may extract a multimodal feature vector from the image of the acquired un-labelled dataset, may measure a similarity between the extracted multimodal feature vector of the labelled dataset and the multimodal feature vector of the un-labelled dataset, and may label the un-labelled dataset based on the measured similarity. Accordingly, by creating multimodal training datasets for predicting a user personality by using pseudo-labeling, training datasets may be obtained rapidly, economically and effectively.
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3.发明公开公开(公告)号：US20240193436A1
公开(公告)日：2024-06-13
申请号：US18536589
申请日：2023-12-12
Applicant: Korea Electronics Technology Institute
Inventor： Jae Woong YOO , Hye Dong JUNG , Mi Ra LEE
CPC classification number: G06N5/02 , G06V40/176 , G06V40/20
Abstract: There is provided a user personality prediction method using pre-obtained personality indicators and time-series information. According to an embodiment, a personality prediction method may acquire personality indicators representing personalities of a user, may acquiring external features of the user as time-series data, may train a personality prediction model with correlations between the acquired external features and the personality indicators, and may predict personality indicators of the user from the external features of the user by using the trained personality prediction model. Accordingly, a personality of a user is predicted in real time based on external features extracted in real time, and hence, personality prediction may be performed flexibly in response to a subtle change in AU intensities acquired as time-series data.
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公开(公告)号：US20240193376A1
公开(公告)日：2024-06-13
申请号：US18536853
申请日：2023-12-12
Applicant: Korea Electronics Technology Institute
Inventor： Jae Woong YOO , Hye Dong JUNG , Mi Ra LEE
IPC: G06F40/40 , H04L67/1396
CPC classification number: G06F40/40 , H04L67/1396
Abstract: There is provided a customized personality agent system evolving according to a satisfaction of a user. An interactive service providing method according to an embodiment provides an interactive AI service to a user by using an agent that is selected from a plurality of agents based on a state of personality of the user, and evaluates a satisfaction of the user and trains the agent that provides the interactive service. Accordingly, by searching an agent that has an optimal personality suited to a state of personality of a user and providing an interactive AI service, service quality may be enhanced. Also, by rewarding and training an agent that provides a service based on a satisfaction of a user who receives the service, the personality of the agent may evolve to be well suited to a personality of the user.
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