Abstract: An example method comprises: receiving a natural language text; transforming, by a neural network, the natural language text into a numeric representation comprising a plurality of numeric values; discarding the natural language text; and performing, using the numeric representation of the natural language text, an information extraction task.

Abstract: An example method of employee experience and efficiency evaluation based on the employee's collaboration circles comprises: identifying, by a computer system, based on processing a plurality of documents reflecting communications of a specified person, a collaboration circle of the specified person; generating, based on a set of previously collected responses reflecting experience and efficiency of the employee, a set of questions with respect to experience and efficiency of the employee; presenting the set of questions to a plurality of persons comprised by the collaboration circle; collecting responses to the set of questions from the plurality of persons comprised by the collaboration circle; and generating a dashboard reflecting the collected responses.

Abstract: A method to predict problematic actions in an organization, executed by a processing device, includes accessing stored employee-related data, such as at least one of emails, surveys, minutes, or records of conversations, identifying a subset of the employee-related data that is associated with an employee, and predicting, based on the subset of the employee-related data associated with the employee, at least one of a likelihood that the employee is engaged in an adverse relation with other employees or a likelihood that the employee is to resign from the organization within a period of time.

Abstract: A task assistant identifies a correspondence received by a source associated with a user and determines that the correspondence includes a request. The task assistant further determines a ranking associated with the request based on one or more characteristics of the request and of the correspondence. In response to the ranking of the request exceeding a threshold, the task assistant generates a notification associated with the request and provides the notification to a client device associated with the user.

Abstract: An example method comprises: receiving a natural language text; transforming, by a neural network, the natural language text into a numeric representation comprising a plurality of numeric values; discarding the natural language text; and performing, using the numeric representation of the natural language text, an information extraction task.

Abstract: A task assistant identifies a correspondence received by a source associated with a user and determines that the correspondence includes a request. The task assistant further determines a ranking associated with the request based on one or more characteristics of the request and of the correspondence. In response to the ranking of the request exceeding a threshold, the task assistant generates a notification associated with the request and provides the notification to a client device associated with the user.

Abstract: A task assistant identifies a correspondence received by a source associated with a user and determines that the correspondence includes a request. The task assistant further determines a ranking associated with the request based on one or more characteristics of the request and of the correspondence. In response to the ranking of the request exceeding a threshold, the task assistant generates a notification associated with the request and provides the notification to a client device associated with the user.

Abstract: A method to predict problematic actions in an organization, executed by a processing device, includes accessing stored employee-related data, such as at least one of emails, surveys, minutes, or records of conversations, identifying a subset of the employee-related data that is associated with an employee, and predicting, based on the subset of the employee-related data associated with the employee, at least one of a likelihood that the employee is engaged in an adverse relation with other employees or a likelihood that the employee is to resign from the organization within a period of time.

Abstract: A task assistant executed by a processing device receives a copy of a first correspondence sent by a first user in a first communication thread, wherein the first correspondence is addressed to a second user and the copy is sent to an automated task assistant. The task assistant determines that the first correspondence includes a request and a due date and monitors additional correspondence in the first communication thread to determine whether the request has been satisfied by the due date. Responsive to determining that the request has not been satisfied, the task assistant provides a notification with a reminder of the request to a client device associated with the second user in advance of the due date.

Abstract: A task assistant identifies a correspondence received by a source associated with a user and determines that the correspondence includes a request. The task assistant further determines a ranking associated with the request based on one or more characteristics of the request and of the correspondence. In response to the ranking of the request exceeding a threshold, the task assistant generates a notification associated with the request and provides the notification to a client device associated with the user.

Abstract: A system and method for providing individualized tsunami notifications with the aid of a digital computer are provided. A request for a location of a mobile device is received by a mobile application executing on the mobile device. The location is provided to at least one server. A notification of a possible forecasted tsunami impact on an area that comprises the provided location is received via the communication network, the notification comprising a vector line applicable to a map of the area and describing a portion of the area forecasted to be impacted when applied to the map. The vector line is applied to the map and the portion of the area is represented on the map. When the location is forecasted to be impacted is calculated. The representation of the portion of the area and when the location is forecasted to be impacted is represented via the mobile device.

Abstract: A system and method for providing individualized tsunami notifications with the aid of a digital computer are provided. A request for a location of a mobile device is received by a mobile application executing on the mobile device. The location is provided to at least one server. A notification of a possible forecasted tsunami impact on an area that comprises the provided location is received via the communication network, the notification comprising a vector line applicable to a map of the area and describing a portion of the area forecasted to be impacted when applied to the map. The vector line is applied to the map and the portion of the area is represented on the map. When the location is forecasted to be impacted is calculated. The representation of the portion of the area and when the location is forecasted to be impacted is represented via the mobile device.

Abstract: A pinpoint forecast of the possible impact of a tsunami is created by processing near real-time tsunami data, including seismic data or wave data obtained using underwater pressure sensors, bathymetry data of the body of water in which the tsunami occurs, and topographic data of specific locations. Notifications are provided to subscribers via their mobile devices. The forecast presents the notification in a form that is easily understandable and which allows the subscriber to take any appropriate action. Disaster response personnel responsible for warning the populace can be similarly notified in a further embodiment. Additional assistance can be provided by activating disaster response and notification devices in the specific locations to be impacted. By providing the location-specific notifications and other actionable data, the system and method clarifies precisely where danger due to the tsunami exists on an individual basis and simplifies the evacuation from the affected areas, aiding public safety.