Abstract: An information processing apparatus (100) includes a generation unit (102) generating an optimization model (80) by using template information (10) defining an objective function and a constraint that are indicators of an optimization problem, wherein the template information (10) includes item definition information (12) determining data items input to the objective function and the constraint, and algorithm definition information (14) defining an algorithm for the objective function and the constraint.

Abstract: Template information (10) includes item definition information (12) determining an item of each piece of input data utilized for generation of a predictive model, algorithm definition information (14) determining a generation algorithm of a predictive model, and view definition information (16) determining a display aspect of information relating to a predictive model. An analysis system (2000) accepts specification of the template information (10). Moreover, the analysis system (2000) accepts, regarding each item determined by the item definition information (12) of the template information (10), specification of input data being associated with the item. Further, the analysis system (2000) processes input data by an algorithm determined by the algorithm definition information (14) of the template information (10), and generates a predictive model.

Abstract: A prediction result output unit 81 outputs a prediction result in which a predicted value and an actual value are associated with each other, in a predetermined series. An input unit 82 accepts from a user a designation of the prediction result in the output series. A basis output unit 83 outputs a basis for the predicted value in the prediction result for the accepted designation. The basis output unit 83 outputs, as the basis for the predicted value, a product value for each of explanatory variables in a prediction formula used for the prediction, the product value being calculated by multiplying a value of an explanatory variable by a coefficient of the explanatory variable.

Abstract: An information processing apparatus according to the present invention divides a period in which performance data at a business facility as a prediction target is present into a plurality of partial periods. The information processing apparatus performs prediction processing using each of a plurality of prediction models for a second partial period which is a partial period other than a first partial period including a start time of a predetermined period, and compares the result of the process with the performance data in a partial period as a target of the prediction processing. The information processing apparatus decides a prediction model to be used for sales prediction for a period subsequent to the predetermined period on the basis of the result of the comparison.

Abstract: This invention discloses a shipment-volume prediction device that predicts the shipment volumes of products at a new store. A classification unit (90) classifies a plurality of existing stores into a plurality of clusters. On the basis of information regarding the new store, a cluster estimation unit (91) estimates which cluster the new store will belong to. A shipment-volume prediction unit (92) estimates the shipment volumes of products at the new store by computing predicted shipment volumes for said products at existing stores that belong to the same cluster as the new store.

Abstract: This invention discloses a product recommendation device that recommends products that are selling well in many stores, not products that are selling well in only some stores. For each of a plurality of products sold at a plurality of stores, a score computation unit (90) computes a score that increases as a function of both shipment volume and the number of stores at which the product in question is being dealt. A product recommendation unit (91) recommends products that have higher scores than products being dealt at the store for which the recommendation is being made.