Abstract: Engagement signals may be generated and analyzed based on user interactions with documents, particularly in a collaboration environment. The user interactions may generate raw collaboration signals that may be received and processed into cleaned collaboration signals. For example, noise may be removed from the raw collaboration signals to generate the cleaned collaboration signals. The cleaned collaboration signals may be grouped into engagement signals, where each engagement signal represents an individual event or engagement event of the user with the document. The grouping may be based on boundary signals, time frames, and/or any other reasonable limiting element. Each of the engagement signals may be classified into one of several engagement types based on the cleaned collaboration signals in the engagement signal. The engagement signals may then be analyzed to make determinations, recommendations, or the like regarding one or more users of the document, the document content, or the like.

Abstract: A data processing system implements receiving a first textual prompt from a first user via a first user interface of a first client device, the first textual prompt includes a textual description of content to be generated by a generative model; providing the first textual prompt as a first input to the generative model to obtain as an output first collaborative content based on the first textual prompt; receiving an edited version of the first collaborative content from the first client device that includes edits to the first collaborative content provided by the first user; providing the edited version of the first collaborative content as a second input to the generative model to obtain as an output second collaborative content based on the edited version of the first collaborative content; and causing the first client device to present the second collaborative content on the first user interface.

Abstract: A data processing system implements receiving a first textual prompt from a first user via a first user interface of a first client device, the first textual prompt includes a textual description of content to be generated by a generative model; providing the first textual prompt as a first input to the generative model to obtain as an output first collaborative content based on the first textual prompt; receiving an edited version of the first collaborative content from the first client device that includes edits to the first collaborative content provided by the first user; providing the edited version of the first collaborative content as a second input to the generative model to obtain as an output second collaborative content based on the edited version of the first collaborative content; and causing the first client device to present the second collaborative content on the first user interface.

Abstract: A method for managing annotation surfaces for a document includes receiving a request to add a note to a document, displaying a first user interface (UI) surface for the note, the first UI surface including an editable surface that is editable by a plurality of users and the first UI surface enabling visibility of content to the plurality of users in real-time, and attaching a second UI surface to the first UI surface, the second UI surface being a UI surface for a comment and the second surface UI surface requiring user action for posting the comment.

Abstract: A method for managing annotation surfaces for a document includes receiving a request to add a note to a document, displaying a first user interface (UI) surface for the note, the first UI surface including an editable surface that is editable by a plurality of users and the first UI surface enabling visibility of content to the plurality of users in real-time, and attaching a second UI surface to the first UI surface, the second UI surface being a UI surface for a comment and the second surface UI surface requiring user action for posting the comment.

Abstract: Engagement signals may be generated and analyzed based on user interactions with documents, particularly in a collaboration environment. The user interactions may generate raw collaboration signals that may be received and processed into cleaned collaboration signals. For example, noise may be removed from the raw collaboration signals to generate the cleaned collaboration signals. The cleaned collaboration signals may be grouped into engagement signals, where each engagement signal represents an individual event or engagement event of the user with the document. The grouping may be based on boundary signals, time frames, and/or any other reasonable limiting element. Each of the engagement signals may be classified into one of several engagement types based on the cleaned collaboration signals in the engagement signal. The engagement signals may then be analyzed to make determinations, recommendations, or the like regarding one or more users of the document, the document content, or the like.

Abstract: The present disclosure is directed to automated notification generation, where a generated notification comprises a live representation of a content update that is linked and synchronized with a distributed collaborative canvas (or other source content) comprising the content portion which is being updated. A non-limiting example of a content update is a message notification, such as an at-mention (@mention), that is included inline within a content portion. Other triggers for automated notification generation are also described. Generation of an exemplary notification comprises a contextual relevance analysis that not only selects, for a recipient of the message notification, a specific host application/service endpoint to present the notification in but also determines how/what specific content to present inline within the selected host application/service endpoint.

Abstract: A method and system for providing keyword suggestions to a user of a document during use of the document, the keyword suggestions being made to enable selection of the keywords as tags for the document. The method includes examining contents of a document, identifying a keyword related to the document based at least in part on the contents of the document, displaying the keyword on a user interface element relating to the document to enable a user to choose to add the keyword as a tag associated with the document, receiving an input indicating a user's approval of the keyword, and upon receiving the input, associating the keyword with the document as a tag.

Abstract: A method and system for providing keyword suggestions to a user of a document during use of the document, the keyword suggestions being made to enable selection of the keywords as tags for the document. The method includes examining contents of a document, identifying a keyword related to the document based at least in part on the contents of the document, displaying the keyword on a user interface element relating to the document to enable a user to choose to add the keyword as a tag associated with the document, receiving an input indicating a user's approval of the keyword, and upon receiving the input, associating the keyword with the document as a tag.

Abstract: The generation of sample string font files comprises identifying a language supported by a given font, rendering a sample textual content for that language in that font, encoding the rendered sample textual content as a single, cohesive glyph, storing that glyph in a sample string font file and then recording, within one or more tables, a correspondence between the language, the font and that location. A sample string font file comprises glyphs that are sample textual content of a single language rendered in multiple different fonts, glyphs that are sample textual content of multiple languages rendered in a same font which supports all of those different languages, or combinations thereof. Appropriate sample string font files are downloaded to a local computing device in accordance with user interface language settings, and the sample textual content, as rendered in different fonts, is presented through font selection user interface mechanisms.