Abstract: This application relates to apparatus and methods for automatically grouping the same or similar items provided by various suppliers that may use various supplier identification systems to identify the items to a retailer. In some examples, item update data identifying an attribute of an item is received and an anomaly is detected in a hierarchical structure of a database. The anomaly is detected by a machine learning model trained by a supervised training dataset based on attributes of items. A hierarchical association between the attribute of the item and the item in the database is generated when the detected anomaly includes a difference between a first hierarchical relationship defined in the item update data and a second hierarchical relationship defined for the item in the database. Item data including the hierarchical association is transmitted to update at least one marketplace.

Abstract: This application relates to apparatus and methods for automatically grouping the same or similar items provided by various suppliers that may use various supplier identification systems to identify the items to a retailer. In some examples, a computing device receives a supplier identifier from a supplier. The supplier identifier identifies an item that the supplier provides to the retailer for sale. The computing device may determine a group identifier for the item, where the group identifier identifies the item within a group of the retailer. The computing device may update the supplier identifier's association to the retailer identifier based on whether the group identifier is also associated with the retailer identifier. In some examples, the computing device executes a machine learning model to determine anomalies within a current database of supplier identifiers and associated retailer identifiers. In some examples, the computing device indicates changes to associations and any detected anomalies.

Abstract: This application relates to apparatus and methods for automatically grouping the same or similar items provided by various suppliers that may use various supplier identification systems to identify the items to a retailer. In some examples, a computing device receives a supplier identifier from a supplier. The supplier identifier identifies an item that the supplier provides to the retailer for sale. The computing device may determine a group identifier for the item, where the group identifier identifies the item within a group of the retailer. The computing device may update the supplier identifier's association to the retailer identifier based on whether the group identifier is also associated with the retailer identifier. In some examples, the computing device executes a machine learning model to determine anomalies within a current database of supplier identifiers and associated retailer identifiers. In some examples, the computing device indicates changes to associations and any detected anomalies.

Abstract: A device can receive, from a set of storage devices, first information relating to one or more pilot data plans that are associated with one or more first groups of user devices. The device can receive, from the set of storage devices, second information relating to one or more live data plans that are associated with one or more second groups of user devices. The device can analyze the first information and/or the second information to identify one or more patterns of information. The one or more patterns can include a data usage pattern, a demographic information pattern, a revenue generation pattern, and/or a user interest pattern. The device can perform one or more actions, including generating a new data plan, identifying one or more user accounts as candidates for a new data plan, and/or transmitting, via a network, information relating to the new data plan.

Abstract: A device may receive, from a user device, a hypertext transfer protocol (HTTP) CONNECT request that includes a uniform resource locator (URL). The device may determine, using a data structure, whether the URL is a sponsored URL or a non-sponsored URL. The data structure may include one or more sponsored URLs associated with a toll-free data service campaign. The device may establish an HTTP CONNECT tunnel for transferring traffic, associated with the URL, between the user device and another device. The device may monitor data use, associated with the HTTP CONNECT tunnel, based on determining whether the URL is a sponsored URL or a non-sponsored URL. The device may generate a traffic information record based on monitoring the data use, and the device may provide the traffic information record to the user device.

Abstract: A device can receive, from a set of storage devices, first information relating to one or more pilot data plans that are associated with one or more first groups of user devices. The device can receive, from the set of storage devices, second information relating to one or more live data plans that are associated with one or more second groups of user devices. The device can analyze the first information and/or the second information to identify one or more patterns of information. The one or more patterns can include a data usage pattern, a demographic information pattern, a revenue generation pattern, and/or a user interest pattern. The device can perform one or more actions, including generating a new data plan, identifying one or more user accounts as candidates for a new data plan, and/or transmitting, via a network, information relating to the new data plan.

Abstract: A device may receive, from a user device, a hypertext transfer protocol (HTTP) CONNECT request that includes a uniform resource locator (URL). The device may determine, using a data structure, whether the URL is a sponsored URL or a non-sponsored URL. The data structure may include one or more sponsored URLs associated with a toll-free data service campaign. The device may establish an HTTP CONNECT tunnel for transferring traffic, associated with the URL, between the user device and another device. The device may monitor data use, associated with the HTTP CONNECT tunnel, based on determining whether the URL is a sponsored URL or a non-sponsored URL. The device may generate a traffic information record based on monitoring the data use, and the device may provide the traffic information record to the user device.

Abstract: A device may receive first information. The first information may be based on traffic associated with usage of a toll-free data service. The device may receive an identifier for a user device. The user device may be using the toll-free data service. The device may generate second information. The second information may correspond to usage, by the user device, of the toll-free data service. The second information may be generated based on the first information and the identifier. The device may send the second information to another device to support providing a notification of toll-free data service usage. The notification of toll-free data service usage may be based on the second information.

Abstract: A device may receive first information. The first information may be based on traffic associated with usage of a toll-free data service. The device may receive an identifier for a user device. The user device may be using the toll-free data service. The device may generate second information. The second information may correspond to usage, by the user device, of the toll-free data service. The second information may be generated based on the first information and the identifier. The device may send the second information to another device to support providing a notification of toll-free data service usage. The notification of toll-free data service usage may be based on the second information.