Abstract: Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support intelligent re-use of knowledge (e.g., across an organization) using a natural text-based querying framework. A knowledge representation of prior work performed for the organization may be generated based on organizational knowledge (e.g., historical work record data that identifies a plurality of work items across an organization). The knowledge representation may include individual work-record entities for each respective work item and individual knowledge graphs corresponding to the individual work-record entities. For each individual knowledge graph, operations may be performed to identity and store project name, subgraph, sentence embedding, and word embedding information.

Abstract: In some examples, machine learning based incident classification and resolution may include analyzing an issue associated with performance of a task or operation of an application or a device, and determining, based on the analysis of the issue and based on a machine learning based automated incident resolution model, whether the issue is appropriate for automated resolution. If so, automated resolution of the issue may be implemented to resolve the issue. Alternatively, a machine learning based incident classification model may be used to determine whether an incident associated with the issue is actionable or non-actionable. If the incident is actionable, a machine learning based incident ticket creation and routing model may be used to generate an incident ticket associated with the incident, and determine support personnel selected from a plurality of support personnel to resolve the incident ticket.