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公开(公告)号:US10325220B2
公开(公告)日:2019-06-18
申请号:US14543133
申请日:2014-11-17
Applicant: OATH INC.
Inventor: Jia Li , Yi Chang , Xiangnan Kong
Abstract: At least one label prediction model is trained, or learned, using training data that may comprise training instances that may be missing one or more labels. The at least one label prediction model may be used in identifying a content item's ground-truth label set comprising an indicator for each label in the label set indicating whether or not the label is applicable to the content item.
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公开(公告)号:US10223727B2
公开(公告)日:2019-03-05
申请号:US14518431
申请日:2014-10-20
Applicant: OATH INC.
Inventor: Jen-Hao Hsiao , Nan Liu , Jia Li
Abstract: Disclosed herein is item recommender that uses a model trained using a combination of at least visual item similarity training data and social activity training data. The model may be used, for example, to identify a set of recommended products having similar visual features as a given product. The set of recommended products may be presented to the user along with the given product. The model may be continuously updated using feedback from users to identify the features considered to be important to the users relative to other features.
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公开(公告)号:US10102227B2
公开(公告)日:2018-10-16
申请号:US15924923
申请日:2018-03-19
Applicant: OATH INC.
Inventor: Jia Li , Nadav Golbandi , XianXing Zhang
Abstract: Disclosed herein is a system and method that facilitate searching and/or browsing of images by clustering, or grouping, the images into a set of image clusters using facets, such as without limitation visual properties or visual characteristics, of the images, and representing each image cluster by a representative image selected for the image cluster. A map-reduce based probabilistic topic model may be used to identify one or more images belonging to each image cluster and update model parameters.
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公开(公告)号:US11151630B2
公开(公告)日:2021-10-19
申请号:US14325192
申请日:2014-07-07
Applicant: Oath Inc.
Inventor: JenHao Hsiao , Jia Li
Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to facilitate or support one or more processes and/or operations for one or more on-line recommendations, such as product-related recommendations, for example.
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公开(公告)号:US10204090B2
公开(公告)日:2019-02-12
申请号:US15651822
申请日:2017-07-17
Applicant: OATH INC.
Inventor: Jia Li , Xiangnan Kong
Abstract: System, method and architecture for providing improved visual recognition by modeling visual content, semantic content and an implicit social network representing individuals depicted in a collection of content, such as visual images, photographs, etc., which network may be determined based on co-occurrences of individuals represented by the content, and/or other data linking the individuals. In accordance with one or more embodiments, using images as an example, a relationship structure may comprise an implicit structure, or network, determined from co-occurrences of individuals in the images. A kernel jointly modeling content, semantic and social network information may be built and used in automatic image annotation and/or determination of relationships between individuals, for example.
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公开(公告)号:US11645860B2
公开(公告)日:2023-05-09
申请号:US15463774
申请日:2017-03-20
Applicant: Oath Inc.
Inventor: Suleyman Cetintas , Kuang-chih Lee , Jia Li
IPC: G06K9/62 , G06F3/04842 , G06F16/58 , G06V10/44 , G06V20/10 , G06V30/413 , G06N3/08
CPC classification number: G06K9/6267 , G06F3/04842 , G06F16/58 , G06K9/6201 , G06K9/626 , G06K9/627 , G06N3/08 , G06V10/454 , G06V20/10 , G06V30/413
Abstract: Briefly, embodiments of methods and/or systems of generating preference indices for contiguous portions of digital images are disclosed. For one embodiment, as an example, parameters of a neural network may be developed to generate object labels for digital images. The developed parameters may be transferred to a neural network utilized to generate signal sample value levels corresponding to preference indices for contiguous portions of digital images.
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公开(公告)号:US10678992B2
公开(公告)日:2020-06-09
申请号:US16418221
申请日:2019-05-21
Applicant: OATH INC.
IPC: G09G5/00 , G06F40/103 , G06T3/40 , G06F16/34
Abstract: Generating notifications comprising text and image data for client devices with limited display screens is disclosed. An image to be included in the notification is resized and reshaped using image processing techniques. The resized image is further analyzed to identify optimal portions for placing the text data. The text data can also be analyzed and shortened for including at the identified portion of resized image to generate a notification. The resulting notification displays the text and image data optimally within the limited screen space of the client device so that a user observing the notification can obtain the information at a glance.
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公开(公告)号:US10318611B2
公开(公告)日:2019-06-11
申请号:US15661105
申请日:2017-07-27
Applicant: OATH INC.
Abstract: Generating notifications comprising text and image data for client devices with limited display screens is disclosed. An image to be included in the notification is resized and reshaped using image processing techniques. The resized image is further analyzed to identify optimal portions for placing the text data. The text data can also be analyzed and shortened for including at the identified portion of resized image to generate a notification. The resulting notification displays the text and image data optimally within the limited screen space of the client device so that a user observing the notification can obtain the information at a glance.
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公开(公告)号:US20180210898A1
公开(公告)日:2018-07-26
申请号:US15924923
申请日:2018-03-19
Applicant: OATH INC.
Inventor: Jia Li , Nadav Golbandi , XianXing ZHANG
CPC classification number: G06F17/30274 , G06F17/30253 , G06F17/30256 , G06F17/30687 , G06F17/30713 , G06K9/4642 , G06K9/6223 , G06K9/6226 , G06K9/6262
Abstract: Disclosed herein is a system and method that facilitate searching and/or browsing of images by clustering, or grouping, the images into a set of image clusters using facets, such as without limitation visual properties or visual characteristics, of the images, and representing each image cluster by a representative image selected for the image cluster. A map-reduce based probabilistic topic model may be used to identify one or more images belonging to each image cluster and update model parameters.
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