Abstract: A method includes obtaining a plurality of content items of a content creator and associated content item metrics. The method further includes identifying, based on the plurality of content items and associated content item metrics, an output of a generative machine learning model that is trained on a subset of content items with content item metrics satisfying one or more scoring criteria. The output of the generative machine learning model provides a representation for an additional content item. The additional content item, when created based on the representation, is predicted to have one or more content item metrics that satisfy the one or more scoring criteria. The method further includes providing for presentation to the content creator the representation for the additional content item.

Abstract: The present invention is notably directed to computerized method for detecting parking-related events from a mobile device. The latter comprising a pressure sensor and a peak detection module. The method comprises: monitoring pressure sensor data from the pressure sensor, the pressure sensor data representative of a pressure variation over a period of time; and comparing the monitored pressure sensor data with reference pressure data corresponding to pressure variations over time as occurring inside a vehicle when, on the one hand, opening a door and, on the other hand, closing a door of this vehicle, to detect a corresponding pressure variation in the monitored pressure sensor data, in order to determine whether a vehicle has parked or has started, wherein the steps of monitoring and comparing are performed by the peak detection module, in the vehicle. The present invention is further directed to related devices and computer program products.

Abstract: The present invention is notably directed to computerized method for detecting parking-related events from a mobile device. The latter comprising a pressure sensor and a peak detection module. The method comprises: monitoring pressure sensor data from the pressure sensor, the pressure sensor data representative of a pressure variation over a period of time; and comparing the monitored pressure sensor data with reference pressure data corresponding to pressure variations over time as occurring inside a vehicle when, on the one hand, opening a door and, on the other hand, closing a door of this vehicle, to detect a corresponding pressure variation in the monitored pressure sensor data, in order to determine whether a vehicle has parked or has started, wherein the steps of monitoring and comparing are performed by the peak detection module, in the vehicle. The present invention is further directed to related devices and computer program products.

Abstract: A service type repository is populated with types of services exposed on a network that has a dynamic organization. The services are embedded on one or more devices included in the network and the services providing information about the one or more devices. A query is received that includes a request for a type of service, and the requested type of service is compared to the types of services in the service type repository to select a collection of matching service types that satisfy the request. Active instances of services that have a type included in the collection of matching service types are identified. The active instances are instances of services embedded on one or more devices included in the network. When no active instances are identified, active instances of services that have a type included in the collection of matching service types are discovered.

Abstract: A service type repository is populated with types of services exposed on a network that has a dynamic organization. The services are embedded on one or more devices included in the network and the services providing information about the one or more devices. A query is received that includes a request for a type of service, and the requested type of service is compared to the types of services in the service type repository to select a collection of matching service types that satisfy the request. Active instances of services that have a type included in the collection of matching service types are identified. The active instances are instances of services embedded on one or more devices included in the network. When no active instances are identified, active instances of services that have a type included in the collection of matching service types are discovered.