Abstract: Embodiments of the present disclosure relate generally to systems for presenting content suggestions within a messaging interface. A content suggestion system performs operations that include: receiving inputs that include a text string into a messaging interface; parsing a keyword from the text string of the input in response to receiving the inputs; retrieving message content that includes at least a media item based on the keyword; and presenting a chat suggestion that includes the message content within the messaging interface, according to certain example embodiments.

Abstract: Example embodiments described herein relate to an icon based tagging system to associate a graphical icon (e.g., an emoji) with a data category, receive media content that includes a data object and the graphical icon, assign the media content to the data category based on the presence of the graphical icon within the media content, receive a search request that comprises search criteria that includes at least the graphical icon, and present a set of search results that include the media content in response to the search request.

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.

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.

Abstract: Example embodiments described herein relate to an icon based tagging system to associate a graphical icon (e.g., an emoji) with a data category, receive media content that includes a data object and the graphical icon, assign the media content to the data category based on the presence of the graphical icon within the media content, receive a search request that comprises search criteria that includes at least the graphical icon, and present a set of search results that include the media content in response to the search request.

Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can be assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

Abstract: A machine learning system can generate an image mask (e.g., a pixel mask) comprising pixel assignments for pixels. The pixels can he assigned to classes, including, for example, face, clothes, body skin, or hair. The machine learning system can be implemented. using a convolutional neural network that is configured to execute efficiently on computing devices having limited resources, such as mobile phones. The pixel mask can be used to more accurately display video effects interacting with a user or subject depicted in the image.

Abstract: Systems, devices, media, and methods are presented for graphical icon identification within an image or video stream. The systems and methods receive an image including a graphical icon. The systems and methods identify a set of proposed regions of the image, at least one proposed region of the set of proposed regions containing the graphical icon and extract a set of semantic features for each proposed region of the set of proposed regions. Based on the set of semantic features of the set of proposed regions, the systems and methods identify a set of proposed icons corresponding to the graphical icon included in the image and determine a match between the graphical icon and at least one proposed icon of the set of proposed icons.

Abstract: The invention is directed to systems and methods that utilize artificial intelligence (AI) and big data analytics to autonomously provide personalized and precise nutritional information and recommendations to a user.

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.

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.

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.

Abstract: Example embodiments described herein relate to an icon based tagging system to associate a graphical icon (e.g., an emoji) with a data category, receive media content that includes a data object and the graphical icon, assign the media content to the data category based on the presence of the graphical icon within the media content, receive a search request that comprises search criteria that includes at least the graphical icon, and present a set of search results that include the media content in response to the search request.

Abstract: Example embodiments described herein relate to an icon based tagging system to associate a graphical icon (e.g., an emoji) with a data category, receive media content that includes a data object and the graphical icon, assign the media content to the data category based on the presence of the graphical icon within the media content, receive a search request that comprises search criteria that includes at least the graphical icon, and present a set of search results that include the media content in response to the search request.

Abstract: Systems, devices, media, and methods are presented for graphical icon identification within an image or video stream. The systems and methods receive an image including a graphical icon. The systems and methods identify a set of proposed regions of the image, at least one proposed region of the set of proposed regions containing the graphical icon and extract a set of semantic features for each proposed region of the set of proposed regions. Based on the set of semantic features of the set of proposed regions, the systems and methods identify a set of proposed icons corresponding to the graphical icon included in the image and determine a match between the graphical icon and at least one proposed icon of the set of proposed icons.

Abstract: A content suggestion system to generate and cause display of a set of chat suggestions based on messages received at a client device. The content suggestions system is configured to display messages that include message content at a client device, and identify content selected by a user of the client device to be included in a response to the messages received at the client device. The content suggestion system tracks and stores a number of times in which a particular pair of content appear in succession in a chat context, and calculates a ranking of the content among a set of available content. When subsequent messages that include the content of the content pair are displayed at the client device, the content suggestion system retrieves and presents a set of content as suggestions, based on the corresponding ranks.

Abstract: Systems, devices, media, and methods are presented for graphical icon identification within an image or video stream. The systems and methods receive an image including a graphical icon. The systems and methods identify a set of proposed regions of the image, at least one proposed region of the set of proposed regions containing the graphical icon and extract a set of semantic features for each proposed region of the set of proposed regions. Based on the set of semantic features of the set of proposed regions, the systems and methods identify a set of proposed icons corresponding to the graphical icon included in the image and determine a match between the graphical icon and at least one proposed icon of the set of proposed icons.

Abstract: A content suggestion system to generate and cause display of a set of chat suggestions based on messages received at a client device. The content suggestions system is configured to display messages that include message content at a client device, and identify content selected by a user of the client device to be included in a response to the messages received at the client device. The content suggestion system tracks and stores a number of times in which a particular pair of content appear in succession in a chat context, and calculates a ranking of the content among a set of available content. When subsequent messages that include the content of the content pair are displayed at the client device, the content suggestion system retrieves and presents a set of content as suggestions, based on the corresponding ranks.

Abstract: Embodiments of the present disclosure relate generally to systems for presenting content suggestions within a messaging interface. A content suggestion system performs operations that include: receiving inputs that include a text string into a messaging interface; parsing a keyword from the text string of the input in response to receiving the inputs; retrieving message content that includes at least a media item based on the keyword; and presenting a chat suggestion that includes the message content within the messaging interface, according to certain example embodiments.

Abstract: Embodiments of the present disclosure relate generally to systems for presenting content suggestions within a messaging interface. A content suggestion system performs operations that include: receiving inputs that include a text string into a messaging interface; parsing a keyword from the text string of the input in response to receiving the inputs; retrieving message content that includes at least a media item based on the keyword; and presenting a chat suggestion that includes the message content within the messaging interface, according to certain example embodiments.