Abstract: Various embodiments herein described are directed to methods, apparatuses and computer program products configured for improving human-computer interactions and interfaces in integrated service and asset management platforms. In some embodiments, an integrated service and asset management platform may generate and store ticket data objects (for example, incident ticket data objects and/or change ticket data objects). When a new ticket data object (for example, an incident ticket data object and/or a change ticket data object) is received by the integrated service and asset management platform, the integrated service and asset management platform may select one or more related ticket data objects. Additional example embodiments provide various example incident and change management user interfaces that facilitate various user inputs and software operations in the integrated service and asset management platform.

Abstract: Methods, apparatuses, or computer program products provide for processing multi-channel service data objects to initiate automated resolution actions via an intent engine. A first service message object is received via a first communication channel of a plurality of communication channels. The first service message object defines a first feature dataset associated with the first communication channel. Additionally, a second service message object is received via a second communication channel of the plurality of communication channels. The second service message object defines a second feature dataset associated with the second communication channel. Based on the first feature dataset and the second feature dataset, support labels for the first service message object and the second service message object are generated.

Abstract: Methods, apparatuses, or computer program products provide for generating an automated resolution action using a knowledge base system and a trained machine learning model. In some examples, a service message object is received via a communication channel of a plurality of communication channels and the service message object defines a feature dataset associated with a service request for an application framework, a knowledge base system is queried based on the feature dataset, a knowledge base data structure is received from the knowledge base system in response to the query, the knowledge base data structure is input to a machine learning model trained for reading comprehension to generate a resolution data object associated with a service resolution for the service request, and a resolution action is initiated for the service request based on the resolution data object.

Abstract: Methods, apparatuses, or computer program products provide for generating automated resolution actions using intent provided by a trained machine learning model. A service message object via a communication channel of a plurality of communication channels. The service message object defines a feature dataset associated with a service request for an application framework. Additionally, a machine learning model trained for intent recognition is applied to the feature dataset to generate an intent support label for the service message object. The intent support label is then correlated to a resolution data object related to a service resolution for the service request. Based on whether the resolution data object satisfies defined resolution criteria for the intent support label, a resolution action for the service request is initiated.

Abstract: Methods, apparatuses, or computer program products provide for processing multi-channel service data objects to initiate automated resolution actions via an intent engine. A first service message object is received via a first communication channel of a plurality of communication channels. The first service message object defines a first feature dataset associated with the first communication channel. Additionally, a second service message object is received via a second communication channel of the plurality of communication channels. The second service message object defines a second feature dataset associated with the second communication channel. Based on the first feature dataset and the second feature dataset, support labels for the first service message object and the second service message object are generated.

Abstract: Various embodiments herein described are directed to methods, apparatuses and computer program products configured for improving human-computer interactions and interfaces in integrated service and asset management platforms. In some embodiments, an integrated service and asset management platform may generate and store ticket data objects (for example, incident ticket data objects and/or change ticket data objects). When a new ticket data object (for example, an incident ticket data object and/or a change ticket data object) is received by the integrated service and asset management platform, the integrated service and asset management platform may select one or more related ticket data objects. Additional example embodiments provide various example incident and change management user interfaces that facilitate various user inputs and software operations in the integrated service and asset management platform.

Abstract: A computer-implemented method is disclosed. The method comprises receiving a notification from a job scheduler that an execution time for a job registered with the job scheduler is at or before a first time being a current time. The method also comprises identifying, in response to receiving the notification, at least one task from a task data structure with a target runtime that is at or before the first time. The task data structure stores task data for one or more tasks received from one or more client computers, and the task data associates each of the one or more tasks with a target runtime. The method further comprises initiating execution for each of the at least one task and determining whether there is a specific task from the task data structure with a specific target runtime after the first time.

Abstract: A computer-implemented method is disclosed. The method comprises receiving a notification from a job scheduler that an execution time for a job registered with the job scheduler is at or before a first time being a current time. The method also comprises identifying, in response to receiving the notification, at least one task from a task data structure with a target runtime that is at or before the first time. The task data structure stores task data for one or more tasks received from one or more client computers, and the task data associates each of the one or more tasks with a target runtime. The method further comprises initiating execution for each of the at least one task and determining whether there is a specific task from the task data structure with a specific target runtime after the first time.

Abstract: Disclosed herein is a computer implemented method for scheduling a new task. The method comprises: receiving task data in respect of the new task, the task data comprising at least information enabling the new task to be uniquely identified and a target runtime for the new task; recording the received task data in a data structure and determining if a new job needs to be registered with an underlying job scheduler.

Abstract: Disclosed herein is a computer implemented method for scheduling a new task. The method comprises: receiving task data in respect of the new task, the task data comprising at least information enabling the new task to be uniquely identified and a target runtime for the new task; recording the received task data in a data structure and determining if a new job needs to be registered with an underlying job scheduler.

Abstract: Disclosed herein is a computer implemented method for scheduling a new task. The method comprises: receiving task data in respect of the new task, the task data comprising at least information enabling the new task to be uniquely identified and a target runtime for the new task; recording the received task data in a data structure and determining if a new job needs to be registered with an underlying job scheduler.

Abstract: Disclosed herein is a computer implemented method for scheduling a new task. The method comprises: receiving task data in respect of the new task, the task data comprising at least information enabling the new task to be uniquely identified and a target runtime for the new task; recording the received task data in a data structure and determining if a new job needs to be registered with an underlying job scheduler.