Salesforce, Inc.

Slack Technologies, Inc.

Aaron J Maurer

Andrew S Morrison

Adam Jamison Oliner

Renaud Bourassa-Denis

Sohom Paul

Mckenna Lowry

Curtis Neil Allen, Jr

Jacquelyn Rocca

Alexander Nicholas Johnson

Zhifeng Deng

Omar Lee

Leigh Ann Johnson

Katherine Jane Steigman

Lichen Ni

Zachary Alan Kaarvik

David Barrett-Kahn

Wii Yatani

Kelly Holmes Moran

Leonard Jackson Shearer

Serguei Mourachov

Anuj Nair

Jenna Zeigen

Sameera Thangudu

Natalie Qabazard

Denis Sodol

Grace Danielle Ellen Atwood

Anirban Mukhopadhyay

Yiling Chen

Kyle Jablon

Andy Timmons

Ryan Slama

Jake Polacek

Techniques for determining and/or displaying summarized messages are discussed herein. A user may post a message to a virtual space of a communication platform. That is, a user may send a message to one or more users via a virtual space. In such instances, the communication platform may identify the intended recipients of the message and input the message and the intended recipients into a machine-learning model to receive, as output from the machine-learning model, data indicative of a summarized representation of the message. The summary may include information that is relevant and/or important for the intended recipient user(s). Further, the summary may include a summary of the message, action items included in the message, recommendations, and/or any other information. In some examples, the communication platform may cause the summary to be displayed via a user interface of the recipient user.

Displaying a summary based on exchanging messages

Techniques for generating and displaying a summary of multiple virtual spaces are discussed herein. A communication platform may determine whether to generate a summary of the content posted across a set of virtual spaces. For instance, the communication platform can identify a set of virtual spaces that the user is a member of. For a pre-determined period, the communication platform can determine a first number of content items posted to the set of virtual spaces. The communication platform may also determine, over the same period, a second number indicating the number of the content items the user has yet to view. Based on the second number meeting or exceeding a threshold, the communication platform may generate a summary for the user. Accordingly, the communication platform may generate a summary of the content posted to the set of virtual spaces and display the summary via a user interface of the user.

Displaying a communication platform summary

Techniques for generating graphical elements via a communication platform are discussed herein. For example, one or more machine-learning models associated with a communication platform may be configured to receive, as input and from a user of the communication platform, a sentiment and/or a graphical element. The machine-learning model may be trained, using prior natural language statements and prior confidence levels associated with previous graphical elements, to output one or more graphical elements associated with the input. The one or more graphical elements may be shared via the communication platform and used to accurately and effectively convey thoughts, emotions, reactions, and ideas, for example.

Machine learning based on graphical element generator for communication platform

An apparatus is provided for outputting suggested query items by a group-based communication platform. The apparatus may include at least one memory and at least one processor configured to detect group-based communication platform query data stored in a memory of the apparatus. The processor is also configured to rank suggested query items based on the group-based communication platform query data. The processor is further configured to detect non-keystroke engagement of a search input interface of the group-based communication platform. The processor is further configured to determine a first subset of the suggested query items based on the ranking of the suggested query items and automatically launch a query suggestion interface including a first subset of the suggested query items in response to detecting the non-keystroke engagement of the search input interface. Corresponding methods and computer program products are also provided.

Methods, apparatuses and computer program products for outputting improved autosuggestions in a group-based communication platform

Methods, systems, apparatuses, devices, and computer program products are described. A group-based communication system may determine timing for sending notifications to users of the group-based communication system to improve the likelihood of the users interacting with the notifications, interacting with other users in the system, or both. For example, the group-based communication system may identify a notification to send to a user, where the user is associated with a user identifier and a workspace identifier in the group-based communication system. The system may dynamically determine a time for sending the notification based on activity data for the user corresponding to the user identifier and activity data for multiple other users corresponding to the workspace identifier (e.g., members of a team with the user). The system may send the notification for display in a user interface of a user device operated by the user at the determined time.

Notification timing in a group-based communication system

Techniques for clustering a plurality of virtual space servers based on communication platform data are discussed herein. In some examples, a user may post a message to a virtual space of a communication platform. The communication platform may transmit the message to virtual space servers configured to manage the virtual space within which the message originated. In such examples, the communication platform may identify clusters of virtual space servers and determine within which cluster the corresponding virtual space server is located. Virtual space servers may be clustered based on attribute data associated with communication platform data. In some examples, the communication platform may send the message to the virtual space server which may send the message to subscribing gateway servers. Further, the gateways servers may send the message to the recipient client devices. The recipient client devices may display the message via a user interface of the communication platform.

Clustering virtual space servers based on communication platform data

Discovery of communication platform features or exposure of such features to the user may include generating embeddings for a variety of types of communication platform content and communications. These embeddings may be used to characterize and compare various communication platform features and ultimately expose these features to a user when the user may not have otherwise encountered them. The embeddings may additionally or alternatively be used to determine a degree of alignment.

Embeddings-based discovery and exposure of communication platform features

Media, methods, and systems are disclosed for optimizing performance of a running application in connection with a group-based communication system. Log data is collected regarding prior metrics for applications that have encountered performance events. Application state information is monitored and a machine-learning model mapping application metrics to performance outcomes predicts whether the running application will encounter a performance event. The machine-learning model mapping application metrics to performance outcomes is trained based on the collected logs. Based on whether a degradation outcome will be impactful, an application performance parameter may be degraded.

Optimizing application performance with machine learning

Discovery of communication platform features or exposure of such features to the user may include generating embeddings for a variety of types of communication platform content and communications. These embeddings may be used to characterize and compare various communication platform features and ultimately expose these features to a user when the user may not have otherwise encountered them. Embeddings may be generated to characterize a user's interactions with a communication platform and/or characterize a channel and the embeddings may be used to expose methods of communicating with the user and/or over the channel.

Growing community of inventors

Washington, DC, United States of America

Aaron J Maurer