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公开(公告)号：US12118464B2
公开(公告)日：2024-10-15
申请号：US17820657
申请日：2022-08-18
Applicant: Snap Inc.
Inventor： Lawrence Jason Muhlstein , Leonardo Ribas Machado das Neves , Yanen Li , Ning Xu
IPC: G06N3/08 , G06F3/0481 , G06F16/22 , G06F3/0488
CPC classification number: G06N3/08 , G06F3/0481 , G06F16/22 , G06F3/0488
Abstract: A neural network system can select content based on user and item content embeddings in an approach that can be updated in real time on the user device without server support. Requests for content sent to the server can include an anonymous user embedding that includes data describing the user's inputs. The content that is nearest to the user embedding in a joint embedding space can be returned as suggested content.
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公开(公告)号：US11853399B2
公开(公告)日：2023-12-26
申请号：US18059928
申请日：2022-11-29
Applicant: Snap Inc.
Inventor： Jianfei Yu , Luis Carlos Dos Santos Marujo , Venkata Satya Pradeep Karuturi , Leonardo Ribas Machado das Neves , Ning Xu , William Brendel
IPC: G06F40/30 , G06F18/2431 , G06N3/08 , G06N20/20 , G06F40/284 , G06N3/045 , G10L25/30 , G06F40/295 , G06F40/279 , G06F40/289 , G10L15/18 , G10L15/06
CPC classification number: G06F18/2431 , G06F40/284 , G06F40/30 , G06N3/045 , G06N3/08 , G06N20/20 , G06F40/279 , G06F40/289 , G06F40/295 , G10L15/06 , G10L15/1807 , G10L15/1815 , G10L15/1822 , G10L25/30
Abstract: Sentiment classification can be implemented by an entity-level multimodal sentiment classification neural network. The neural network can include left, right, and target entity subnetworks. The neural network can further include an image network that generates representation data that is combined and weighted with data output by the left, right, and target entity subnetworks to output a sentiment classification for an entity included in a network post.
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公开(公告)号：US20230385551A1
公开(公告)日：2023-11-30
申请号：US18201075
申请日：2023-05-23
Applicant: Snap Inc.
Inventor： Di Lu , Leonardo Ribas Machado das Neves , Vitor Rocha de Carvalho , Ning Zhang
IPC: G06F40/295 , G06N20/00 , G06N3/08 , G06F40/30
CPC classification number: G06F40/295 , G06N20/00 , G06N3/08 , G06F40/30
Abstract: A caption of a multimodal message (e.g., social media post) can be identified as a named entity using an entity recognition system. The entity recognition system can use a visual attention based mechanism to generate a visual context representation from an image and caption. The system can use the visual context representation to identify one or more terms of the caption as a named entity.
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公开(公告)号：US11750547B2
公开(公告)日：2023-09-05
申请号：US17459161
申请日：2021-08-27
Applicant: Snap Inc.
CPC classification number: H04L51/10 , G06N3/08 , G06V10/40 , G06V10/82 , G06V30/19147 , G06V30/19173 , H04L67/10
Abstract: A caption of a multimodal message (e.g., social media post) can be identified as a named entity using an entity recognition system. The entity recognition system can use an attention-based mechanism that emphasis or de-emphasizes each data type (e.g., image, word, character) in the multimodal message based on each datatypes relevance. The output of the attention mechanism can be used to update a recurrent network to identify one or more words in the caption as being a named entity.
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公开(公告)号：US20230091110A1
公开(公告)日：2023-03-23
申请号：US17820657
申请日：2022-08-18
Applicant: Snap Inc.
Inventor： Lawrence Jason Muhlstein , Leonardo Ribas Machado das Neves , Yanen Li , Ning Xu
IPC: G06F16/22 , G06N3/08 , G06F3/0481
Abstract: A neural network system can select content based on user and item content embeddings in an approach that can be updated in real time on the user device without server support. Requests for content sent to the server can include an anonymous user embedding that includes data describing the user's inputs. The content that is nearest to the user embedding in a joint embedding space can be returned as suggested content.
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Patent Agency Ranking
公开(公告)号：US12174921B2
公开(公告)日：2024-12-24
申请号：US18244543
申请日：2023-09-11
Applicant: Snap Inc.
Inventor： Jianfei Yu , Luis Carlos Dos Santos Marujo , Venkata Satya Pradeep Karuturi , Leonardo Ribas Machado das Neves , Ning Xu , William Brendel
IPC: G06F40/30 , G06F18/2431 , G06F40/284 , G06N3/045 , G06N3/08 , G06N20/20 , G06F40/279 , G06F40/289 , G06F40/295 , G10L15/06 , G10L15/16 , G10L15/18 , G10L25/30
Abstract: Sentiment classification can be implemented by an entity-level multimodal sentiment classification neural network. The neural network can include left, right, and target entity subnetworks. The neural network can further include an image network that generates representation data that is combined and weighted with data output by the left, right, and target entity subnetworks to output a sentiment classification for an entity included in a network post.
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公开(公告)号：US20240354508A1
公开(公告)日：2024-10-24
申请号：US18761154
申请日：2024-07-01
Applicant: Snap Inc.
Inventor： Di Lu , Leonardo Ribas Machado das Neves , Vitor Rocha de Carvalho , Ning Zhang
IPC: G06F40/295 , G06F40/30 , G06N3/08 , G06N20/00
CPC classification number: G06F40/295 , G06F40/30 , G06N3/08 , G06N20/00
Abstract: A caption of a multimodal message (e.g., social media post) can be identified as a named entity using an entity recognition system. The entity recognition system can use a visual attention based mechanism to generate a visual context representation from an image and caption. The system can use the visual context representation to identify one or more terms of the caption as a named entity.
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公开(公告)号：US20230013116A1
公开(公告)日：2023-01-19
申请号：US17945860
申请日：2022-09-15
Applicant: Snap Inc.
Abstract: A machine learning based system can identify an entity as the likely subject of a multimodal message (e.g., a social media post having a short text phrase overlaid on an image) by creating embeddings for an image of the multimodal message and one or more string embeddings from text of the multimodal message. The embeddings can be weighted to maximize information gain, then recombined and compared against a result embedding database to identify an entity as the subject of the multimodal message.
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公开(公告)号：US20210335350A1
公开(公告)日：2021-10-28
申请号：US16948582
申请日：2020-09-24
Applicant: Snap Inc.
Inventor： Leonardo Ribas Machado das Neves , Vitor Silva Sousa , Shubham Vij
IPC: G10L15/18 , G10L15/197 , H04L12/58
Abstract: A messaging system performs trend analysis on content produced by users of the messaging system. The messaging system is configured to extract modifications from content items received from client devices associated with users where the content items are modified using the modifications that comprises a text caption or a media overlay. The messaging system is further configured to determine one or more words from the content items and the extracted modifications and determine a frequency of the one or more words in the content items and the extracted modifications. The messaging system is further configured to determine whether the one or more words is a trend based on the frequency and an aggregate frequency. The messaging system is further configured to in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.
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公开(公告)号：US10788900B1
公开(公告)日：2020-09-29
申请号：US16023912
申请日：2018-06-29
Applicant: Snap Inc.
Inventor： William Brendel , Francesco Barbieri , Xin Chen , Wei Chu , Venkata Satya Pradeep Karuturi , Luis Carlos Dos Santos Marujo , Leonardo Ribas Machado das Neves
IPC: G06F17/27 , G06F3/023 , G06N3/08 , G06K9/62 , G06F3/0481 , H04L12/58 , G06F40/166 , G06F40/274
Abstract: Symbol prediction can be implemented using a multi-task system trained for different tasks. The tasks may include a single symbol prediction, symbol category prediction, and symbol subcategory prediction. Categories of symbols can be generated by clustering sets of training data using a clustering scheme.
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