International Business Machines Corporation

Norton Samuel Augustus Stanley

Josephine E Justin

Jonathan D Dunne

Zachary A Silverstein

Hemant Kumar Sivaswamy

Badekila Ganesh Prashanth Bhat

Srinivasan Nanduri

The illustrative embodiments provide for signature discourse transformation. An embodiment includes detecting a signature discourse of a user by analyzing the user's discourse using corpus linguistics. The embodiment also includes generating computing a collection of words distinct to the user. The embodiment also includes sensing, using tone analysis and a natural language process model, a tone of the collection of words distinct to the user in the signature discourse utterance. The embodiment also includes mapping a cartesian value of the collection of words distinct to the user. The embodiment also includes deriving a signature discourse transformation (SDT) model from the signature discourse utterances, the collection of words, the tone, and the cartesian value. The embodiment also includes transforming, using the signature discourse transformation, an original discourse by the user into an anonymized text.

Signature discourse transformation

In an approach, a processor receives a report of a push notification identified as spam. A processor determines that a threshold number of push notifications identified as spam has been exceeded. A processor, responsive to determining that the threshold number of push notifications identified as spam has been exceeded, performs an action with respect to a sender of the push notification.

Channel to report push notifications as spam

Aspects of the present invention disclose a method, computer program product, and system for providing push notifications to an active device of a user. The method includes one or more processors identifying a push notification for distribution to at least a first user, wherein the first user is associated with at least two computing devices. The method further includes retrieving historical push notification interaction information that includes data of the first user dismissing push notifications on the at least two computing devices and the first user opening push notifications on the at least two computing devices. The method further includes determining a prediction of an active computing device, of the at least two computing devices, for the first user based on the retrieved historical push notification interaction information. The method further includes the push notification to the predicted active computing device of the first user.

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Bengaluru, India

Norton Samuel Augustus Stanley