Abstract: In some examples, sequence, frequency, and time interval based journey recommendation may include generating a plurality of clusters of entities, and generating a network that identifies a time interval to a next interaction that leads to success. An estimated time interval to a specified number of conversions may be determined. A success criterion that represents a positive outcome in the estimated time interval may be determined. A historical sequence of events may be partitioned into a plurality of sequences of events leading to success or failure. The plurality of sequence of events may be mapped based on analyzed probabilities, a determined waiting interval, and determined frequency contributions, and evaluated as to whether a mapped sequence of events duration is less than a planned duration. If so, a journey may be generated and include a determined sequence of events, a corresponding frequency, and a corresponding waiting interval.

Abstract: In some examples, sequence, frequency, and time interval based journey recommendation may include generating a plurality of clusters of entities, and generating a network that identifies a time interval to a next interaction that leads to success. An estimated time interval to a specified number of conversions may be determined. A success criterion that represents a positive outcome in the estimated time interval may be determined. A historical sequence of events may be partitioned into a plurality of sequences of events leading to success or failure. The plurality of sequence of events may be mapped based on analyzed probabilities, a determined waiting interval, and determined frequency contributions, and evaluated as to whether a mapped sequence of events duration is less than a planned duration. If so, a journey may be generated and include a determined sequence of events, a corresponding frequency, and a corresponding waiting interval.