Abstract: A W-graph system comprising a server connected with a plurality of clients via a network. Each client/user performs a design task via a design application while the server collects timestamped event data. The server generates a plurality of W-graphs for a plurality of tasks based on the collected event data. Each W-graph comprises one or more representative workflows, each representative workflow comprising at least one merged node representing nodes from different workflows for different users performing the same task. A W-graph for a task selected by the user may be viewed in a W-graph GUI. A user may also select a W-suggest function to have a current workflow for a task analyzed for optimization based on a W-graph generated for the same task. A modified current workflow is generated that highlights user techniques in the current workflow that are less efficient than user techniques in the W-graph.

Abstract: Systems and methods of identifying groups of actors based on temporal records and outputting groups of vectorized temporal records are provided. A prediction engine receives a vector representing a temporal record comprising an event having a timestamp. The prediction engine generates a probability score of a future event associated with the temporal record. The vector is grouped with one or more additional vectors to form a group, the grouping based on the temporal record and the probability score. The group is then output.

Abstract: A W-graph system comprising a server connected with a plurality of clients via a network. Each client/user performs a design task via a design application while the server collects timestamped event data. The server generates a plurality of W-graphs for a plurality of tasks based on the collected event data. Each W-graph comprises one or more representative workflows, each representative workflow comprising at least one merged node representing nodes from different workflows for different users performing the same task. A W-graph for a task selected by the user may be viewed in a W-graph GUI. A user may also select a W-suggest function to have a current workflow for a task analyzed for optimization based on a W-graph generated for the same task. A modified current workflow is generated that highlights user techniques in the current workflow that are less efficient than user techniques in the W-graph.

Abstract: A W-graph system comprising a server connected with a plurality of clients via a network. Each client/user performs a design task via a design application while the server collects timestamped event data. The server generates a plurality of W-graphs for a plurality of tasks based on the collected event data. Each W-graph comprises one or more representative workflows, each representative workflow comprising at least one merged node representing nodes from different workflows for different users performing the same task. A W-graph for a task selected by the user may be viewed in a W-graph GUI. A user may also select a W-suggest function to have a current workflow for a task analyzed for optimization based on a W-graph generated for the same task. A modified current workflow is generated that highlights user techniques in the current workflow that are less efficient than user techniques in the W-graph.