SERVICE DEMAND POTENTIAL PREDICTION DEVICE
    1.
    发明公开

    公开(公告)号:US20240346532A1

    公开(公告)日:2024-10-17

    申请号:US18689725

    申请日:2022-07-20

    申请人: NTT DOCOMO, INC.

    IPC分类号: G06Q30/0202

    CPC分类号: G06Q30/0202

    摘要: A service demand potential prediction device (10) includes: an acquisition unit (11) for acquiring the number of service provision results for own-company service and other-company service for each area; a calculation unit (12) for calculating a relative index of the own-company service to the other-company service for each area; a selection unit (13) for selecting a dominant area where the own-company service is dominant; a construction unit (14) for constructing a model (M) by performing machine learning using a characteristic amount of the dominant area as an explanatory variable and the number of service provision results of the own-company service as an objective variable; and a prediction unit (15) for predicting a service demand potential of the own-company service when the non-dominant area is assumed to be a dominant area by inputting the characteristic amount of the non-dominant area into the model (M).

    Detecting changes in customer (user) behavior using a normalization value

    公开(公告)号:US12112343B2

    公开(公告)日:2024-10-08

    申请号:US17860277

    申请日:2022-07-08

    申请人: Klaviyo, Inc

    摘要: Apparatuses, methods, and systems for detecting changes in customer behavior are disclosed. One method includes detecting customer action data, receiving, by a marketing platform server, the customer action data over a period of time, determining, customer parameters including a mean, and a standard deviation of the customer action data, generating a normalization value when the standard deviation is detected to be less than a deviation threshold, calculating, by the marketing platform server, a value of deviation from expectation based at least on the mean, the normalization value, and a noise factor, calculating a current cumulative sum value of the customer action data based on a prior cumulative sum value and the value of the deviation from expectation, comparing the current cumulative sum value with a threshold, and generating an electronic communication for the merchant server when the current cumulative sum value satisfies a compared condition with the preselected threshold.

    ROUTE OPTIMIZATION FOR VENDOR IN STADIUM
    7.
    发明公开

    公开(公告)号:US20240330789A1

    公开(公告)日:2024-10-03

    申请号:US18616417

    申请日:2024-03-26

    IPC分类号: G06Q10/047 G06Q30/0202

    CPC分类号: G06Q10/047 G06Q30/0202

    摘要: According to an aspect of the present invention, there is provided a route determination apparatus that has one or more processors that execute a process including: collecting preference information relating to preferences of spectators at an event held at a facility; calculating, from the collected preference information, a demand level for a vendor of products in each seating block in the facility; determining, on the basis of the demand level in each seating block, a route along which the vendor is to move; and adjusting the route such that a position of the vendor moving along the determined route satisfies a predetermined condition.

    COMPUTER OPTIMIZED DETERMINATION OF PRODUCT AVAILABILITY

    公开(公告)号:US20240311719A1

    公开(公告)日:2024-09-19

    申请号:US18184416

    申请日:2023-03-15

    摘要: Generation of an available to promise (ATP) value. A method identifies business constraints and goals for an omnichannel retailer based on input quantitative and qualitative data. The method determines numerical parameters for use in an executable optimization model and using a machine learning model. Additionally, the method builds the executable optimization model using at least one of the goals as a respective at least one objective in the optimization model, at least one of the constraints as a respective at least one constraint in the optimization model, and at least one of the numerical parameters as at least one additional parameter in the executable optimization model. In addition, the method executes the executable optimization model and generates an ATP value, and outputs the ATP value to an e-commerce system.