Abstract: A cluster number setting device includes a memory, and a processor configured to: input time series data representing a state of a system and configured by data of a dimension of the number of devices constituting the system, a dimension of the number of items representing the number of devices×states of the devices, or a dimension of the number of devices×the number of items×a predetermined time window length; repeatedly cluster data constituting the time series data while counting up the number of clusters from 1 or 2; calculate a predetermined index by using a result of the clustering; determine whether the index is less than a preset threshold; and output the current number-1 of clusters as the number of clusters to be set for unsteady fluctuation detection processing that uses clustering processing, when the index is determined to be less than the threshold.

Abstract: A viewing abandonment factor estimation device includes a memory; and a processor configured to include an estimation model for estimating a factor, the estimation model including a plurality of feature quantities measurable for viewing of a video relevant to an adaptive bit rate video distribution as inputs and the factor of the viewing abandonment in the viewing as an output.

Abstract: A viewing abandonment factor estimation device includes a memory; and a processor configured to include an estimation model for estimating a factor, the estimation model including a plurality of feature quantities measurable for viewing of a video relevant to an adaptive bit rate video distribution as inputs and the factor of the viewing abandonment in the viewing as an output.

Abstract: This streaming design assistance method assists in the selection of an encoding condition for increasing the watching time in adaptive bitrate video streaming by causing a computer to execute: estimating a relationship between a watching time or an abandonment rate and an application quality index according to a mathematical model on the basis of an actual value of a watching time of each of a plurality of first sessions related to video streaming and an actual value of an application quality index of each of the sessions; estimating the application quality index of each of the sessions for each of a plurality of encoding conditions related to video streaming on the basis of the plurality of encoding conditions and an actual value of time-series throughput of each of a plurality of second sessions; and applying the application quality index estimated under each of the encoding conditions to the relationship to estimate an average watching time of the plurality of second sessions.

Abstract: This streaming design assistance method assists in the selection of an encoding condition for increasing the watching time in adaptive bitrate video streaming by causing a computer to execute: estimating a relationship between a watching time or an abandonment rate and an application quality index according to a mathematical model on the basis of an actual value of a watching time of each of a plurality of first sessions related to video streaming and an actual value of an application quality index of each of the sessions; estimating the application quality index of each of the sessions for each of a plurality of encoding conditions related to video streaming on the basis of the plurality of encoding conditions and an actual value of time-series throughput of each of a plurality of second sessions; and applying the application quality index estimated under each of the encoding conditions to the relationship to estimate an average watching time of the plurality of second sessions.