Abstract: An email system detects a user interaction to interact with a social media application, within the email system. The email system accesses a social media component that renders a user interface from the social media system and detects interactions with the user interface to generate content for the social media application. The social media component calls the social media application, with the content, and provides a response indicating that the content has been sent to the social media application.

Abstract: An email system detects a user interaction to interact with a social media application, within the email system. The email system accesses a social media component that renders a user interface from the social media system and detects interactions with the user interface to generate content for the social media application. The social media component calls the social media application, with the content, and provides a response indicating that the content has been sent to the social media application.

Abstract: Systems and methods are provided that automatically process a message input, construct an intelligent query based on the processing of the message input, and provide at least one attachable entity according to the processing results and the intelligent query. In some example aspects, a message is received. A natural language processor to determine if the message is requesting content may then process the message. If the message is determined to be requesting content, then candidate sub-queries may be generated to serve as a training set for a query that will be sent to an external search engine to retrieve the attachable entity. The sub-queries may be ranked in order of relevance and performance score. The highest ranked sub-queries may then be used in the actual query that is fired against the external search engine. The external search engine may search local and remote repositories for the top K most relevant attachable entities and present them to a user for attachment in a reply message.

Abstract: A messaging system identifies a received message as a notification message from a conversation system in a media application. The messaging system obtains rendering information to render a current state of the conversation thread represented by the message. The message system renders the current state of the followed conversation thread, with actuators that provide interactive functionality allowing the user to interact with the conversation thread, in the message viewer of the user's messaging system.

Abstract: A messaging system identifies a received message as a notification message from a conversation system in a media application. The messaging system obtains rendering information to render a current state of the conversation thread represented by the message. The message system renders the current state of the followed conversation thread, with actuators that provide interactive functionality allowing the user to interact with the conversation thread, in the message viewer of the user's messaging system.

Abstract: Systems and methods are provided that automatically process message input and provide action responses according to the processing results. The automatic action response system may leverage at least one machine-learning algorithm that is trained using a dataset. The provided action responses may comprise of default action responses and/or intelligent action responses that are based at least in part on prior conversational data between a user and a sender. Some intelligent action responses may include text-based replies, which eliminate the need for a user to type a reply on a device screen, thereby saving previous time, conserving device battery life, and preserving the integrity of the device hardware. A portion of a message may be highlighted manually by a user or automatically by the action response system to initiate the automatic action response system. In this way, a more efficient and productive user experience across various devices and applications is achieved.

Abstract: Systems and methods are provided that automatically process message input and provide action responses according to the processing results. The automatic action response system may leverage at least one machine-learning algorithm that is trained using a dataset. The provided action responses may comprise of default action responses and/or intelligent action responses that are based at least in part on prior conversational data between a user and a sender. Some intelligent action responses may include text-based replies, which eliminate the need for a user to type a reply on a device screen, thereby saving previous time, conserving device battery life, and preserving the integrity of the device hardware. A portion of a message may be highlighted manually by a user or automatically by the action response system to initiate the automatic action response system. In this way, a more efficient and productive user experience across various devices and applications is achieved.

Abstract: Systems and methods are provided that automatically process message input and provide action responses according to the processing results. The automatic action response system may leverage at least one machine-learning algorithm that is trained using a dataset. The provided action responses may comprise of default action responses and/or intelligent action responses that are based at least in part on prior conversational data between a user and a sender. Some intelligent action responses may include text-based replies, which eliminate the need for a user to type a reply on a device screen, thereby saving previous time, conserving device battery life, and preserving the integrity of the device hardware. A portion of a message may be highlighted manually by a user or automatically by the action response system to initiate the automatic action response system. In this way, a more efficient and productive user experience across various devices and applications is achieved.

Abstract: Aspects of the present disclosure relate to systems and methods for providing a preview of protected content in a user interface to an email client. An email client may receive an email message including a uniform resource locator (URL) linked to at least one item stored in a data service. The email client may send the URL to an email server to determine whether a recipient of the URL has permissions to the at least one item stored in the data service. When it is determined that the recipient of the URL has permissions to the at least one item stored in the data service, content for a permission protected preview of the at least one item may be received at the email client. The email client may render the permission protected preview of the at least one item in a user interface to the email client.

Abstract: Aspects of the present disclosure relate to systems and methods for providing a preview of protected content in a user interface to an email client. An email client may receive an email message including a uniform resource locator (URL) linked to at least one item stored in a data service. The email client may send the URL to an email server to determine whether a recipient of the URL has permissions to the at least one item stored in the data service. When it is determined that the recipient of the URL has permissions to the at least one item stored in the data service, content for a permission protected preview of the at least one item may be received at the email client. The email client may render the permission protected preview of the at least one item in a user interface to the email client.

Abstract: Systems and methods are provided that automatically process a message input, construct an intelligent query based on the processing of the message input, and provide at least one attachable entity according to the processing results and the intelligent query. In some example aspects, a message is received. A natural language processor to determine if the message is requesting content may then process the message. If the message is determined to be requesting content, then candidate sub-queries may be generated to serve as a training set for a query that will be sent to an external search engine to retrieve the attachable entity. The sub-queries may be ranked in order of relevance and performance score. The highest ranked sub-queries may then be used in the actual query that is fired against the external search engine. The external search engine may search local and remote repositories for the top K most relevant attachable entities and present them to a user for attachment in a reply message.

Abstract: Systems and methods are provided that automatically process message input and provide action responses according to the processing results. The automatic action response system may leverage at least one machine-learning algorithm that is trained using a dataset. The provided action responses may comprise of default action responses and/or intelligent action responses that are based at least in part on prior conversational data between a user and a sender. Some intelligent action responses may include text-based replies, which eliminate the need for a user to type a reply on a device screen, thereby saving previous time, conserving device battery life, and preserving the integrity of the device hardware. A portion of a message may be highlighted manually by a user or automatically by the action response system to initiate the automatic action response system. In this way, a more efficient and productive user experience across various devices and applications is achieved.