Abstract: A device may receive a query from a user device, and may process the query using a machine learning model to determine categories related to the query. The device may send a message, instructing a user to select a category, to the user device to cause the user device to display the message. The device may receive, from the user device, a selection related to the categories, and may call, based on the selection, a module to cause the module to process the query. The device may receive from the module a response to the query, and may send the response to the user device, to cause the user device to display the response. The device may send the query, the selection, and the response to one or more servers for storage, and may retrain the machine learning model based on information stored by the one or more servers.

Abstract: Described embodiments provide systems and methods for hosted resource configuration, with intelligent personalization of a user's workspace experienced based on the user's available time. The system analyzes the user's schedule, location, and work habits, and prioritizes and maps tasks to available time slots, enabling the system to be more efficient, with less time identifying and selecting next tasks. The system may identify a period of time in which a user can perform a task associated with a hosted application; may identify at least one task associated with the hosted application, the at least one task including a duration within that of the identified period of time, and may provide, to a client device of the user, content of the hosted application based on the identified at least one task, the content enabling the user to accomplish the at least one task within the identified period of time.

Abstract: A device may receive a query from a user device, and may process the query using a machine learning model to determine categories related to the query. The device may send a message, instructing a user to select a category, to the user device to cause the user device to display the message. The device may receive, from the user device, a selection related to the categories, and may call, based on the selection, a module to cause the module to process the query. The device may receive from the module a response to the query, and may send the response to the user device, to cause the user device to display the response. The device may send the query, the selection, and the response to one or more servers for storage, and may retrain the machine learning model based on information stored by the one or more servers.

Abstract: Example embodiments of the present invention relate to a method, a system, and a computer program product for disease outbreak prediction analytics. The method includes calculating a respective correlation value for each outbreak attribute pair among a set of outbreak attributes for a data set regarding a disease and assigning a weight value for each outbreak attribute according to the correlation values. A risk value for the disease then may be determined according to the weight values.