Abstract: Provided is an estimating system including at least one processor configured to: acquire first feature information on each first place of a plurality of first places to which a mobile object is to move in order; input the first feature information on the each first place to a learning model, which has learned a relationship between second feature information on each second place of a plurality of second places to which one of the mobile object and another mobile object has moved in order in the past and an arrival time at the each second place; and acquire an arrival time at the each first place estimated by the learning model.

Abstract: Provided is an estimating system including: at least one memory configured to store computer program code; and at least one processor configured to access said at least one memory and operate according to said computer program code, said computer program code including: via point acquisition code configured to cause the at least one processor to acquire a position of a via point, wherein the route is a path followed by a mobile object when the mobile object moves toward a destination; staying time period code configured to cause the at least one processor to estimate, based on the position of the via point, a staying time period; and arrival time code configured to cause the at least one processor to estimate, by including the staying time period, an arrival time of the mobile object at the destination.

Abstract: An information processing device acquires a reference predicted value that is a predicted value of sales figure of a prediction target period and is calculated based on an actual value of sales figure of a past period corresponding to the prediction target period regarding each of target item groups having a trend that sales figures periodically vary in a predetermined repetition cycle; acquires a value of a contextual parameter envisaged to vary in a period shorter than the repetition cycle and affect the sales figures of the target item groups; calculates a difference value between a predicted value of the sales figure of the prediction target period predicted based on the acquired value of the contextual parameter and the reference predicted value regarding each of the target item groups; and selects an item to be recommended to a user based on the difference value calculated regarding each of the target item groups.

Abstract: Provided is an estimating system including at least one processor configured to: acquire first feature information on each first place of a plurality of first places to which a mobile object is to move in order; input the first feature information on the each first place to a learning model, which has learned a relationship between second feature information on each second place of a plurality of second places to which one of the mobile object and another mobile object has moved in order in the past and an arrival time at the each second place; and acquire an arrival time at the each first place estimated by the learning model.

Abstract: Provided is an estimating system including: at least one memory configured to store computer program code; and at least one processor configured to access said at least one memory and operate according to said computer program code, said computer program code including: via point acquisition code configured to cause the at least one processor to acquire a position of a via point, wherein the route is a path followed by a mobile object when the mobile object moves toward a destination; staying time period code configured to cause the at least one processor to estimate, based on the position of the via point, a staying time period; and arrival time code configured to cause the at least one processor to estimate, by including the staying time period, an arrival time of the mobile object at the destination.