Abstract: Identification of content classes deemed important by users is received. Classifiers are trained on user communication text to recognize content matching content classes. A composite classifier is applied to text of communication among users of a second set of users, including tagging, by the composite classifier, content in text of communication among the users of the second set. The tagging is responsive to the classifiers recognizing their respective content classes in text of communication among the users of the second set.

Abstract: Identification of content classes deemed important by users is received. Classifiers are trained on user communication text to recognize content matching content classes. A composite classifier is applied to text of communication among users of a second set of users, including tagging, by the composite classifier, content in text of communication among the users of the second set. The tagging is responsive to the classifiers recognizing their respective content classes in text of communication among the users of the second set.

Abstract: A method, a computer system, and a computer program product are provided for delivering notifications to users of a messaging platform. A mention directed to a specific context of users is received from a user of a messaging platform. A subset of users is dynamically determined from the specific context of users such that each user of the subset of users is more likely to engage with a notification associated with the mention than users of the specific context of users outside of the subset of users. The notification associated with the mention is sent to only the subset of users from the specific context of users.

Abstract: A method, a computer system, and a computer program product are provided for delivering notifications to users of a messaging platform. A mention directed to a specific context of users is received from a user of a messaging platform. A subset of users is dynamically determined from the specific context of users such that each user of the subset of users is more likely to engage with a notification associated with the mention than users of the specific context of users outside of the subset of users. The notification associated with the mention is sent to only the subset of users from the specific context of users.

Abstract: A method, computer system, and computer program product for cognitively summarizing one or more collaborative moments is provided. An embodiment may include receiving a plurality of communications sent during a collaborative session. The embodiment may also include grouping the plurality of received communications into one or more bursts. The embodiment may further include assigning one or more keywords or one or more entities to each burst. The embodiment may also include generating a summary for each burst using one or more natural language processing techniques based on the assigned one or more keywords or one or more entities. The embodiment may further include transmitting the generated summary to each user participating in the collaborative session.

Abstract: Identification of content classes deemed important by users is received. Classifiers are trained on user communication text to recognize content matching content classes. A composite classifier is applied to text of communication among users of a second set of users, including tagging, by the composite classifier, content in text of communication among the users of the second set. The tagging is responsive to the classifiers recognizing their respective content classes in text of communication among the users of the second set.

Abstract: Identification of content classes deemed important by users is received. Classifiers are trained on user communication text to recognize content matching content classes. A composite classifier is applied to text of communication among users of a second set of users, including tagging, by the composite classifier, content in text of communication among the users of the second set. The tagging is responsive to the classifiers recognizing their respective content classes in text of communication among the users of the second set.

Abstract: Message grouping using temporal and multi-factor similarity includes grouping multiple messages of a corpus in a group messaging system into a number of message bursts. Each message burst includes a number of messages that have a temporal relationship. Multiple of the number of message bursts are grouped into a message cluster. The grouping is based on a similarity of the number of message bursts as defined by multiple features of the message bursts.

Abstract: A method, computer system, and computer program product for cognitively summarizing one or more collaborative moments is provided. An embodiment may include receiving a plurality of communications sent during a collaborative session. The embodiment may also include grouping the plurality of received communications into one or more bursts. The embodiment may further include assigning one or more keywords or one or more entities to each burst. The embodiment may also include generating a summary for each burst using one or more natural language processing techniques based on the assigned one or more keywords or one or more entities. The embodiment may further include transmitting the generated summary to each user participating in the collaborative session.