Abstract:
A method, performed by a mobile device, may include receiving transponder information relating to a consumer product, and verifying whether user consent exists to forward the transponder information to a network device for data mining processing. The method may further include transmitting the transponder information to the network device, when user consent exists.
Abstract:
A method and apparatus for providing labelling information to a third party regarding terminal users in a communication network. A labelling unit receives communication related data generated from executed communications of the terminal users, and fetches stored labelling rules which have been configured specifically for the third party. The labelling unit then converts the communication related data into labelling information, where a communication habits vector is determined by applying the fetched labelling rules on the received communication related data, and the labelling information is determined for the terminal user(s) based on the resulting communication habits vector. The determined labelling information is finally delivered to the third party.
Abstract:
A method and apparatus for providing labelling information to a third party (C) regarding terminal users (210) in a communication network. A labelling unit (200) receives (2:3) communication related data generated from executed communications of the terminal users, and fetches (2:4) stored labelling rules (202) which have been configured (2:1) specifically for the third party. The labelling unit then converts (2:5) the communication related data into labelling information, where a communication habits vector is determined by applying the fetched labelling rules on the received communication related data, and the labelling information is determined for the terminal user(s) based on the resulting communication habits vector. The determined labelling information is finally delivered (2:6) to the third party (C). (Fig. 2)
Abstract:
A device retrieves a first subset (340) of events (e.g. dropped sessions, resource reservation failures, loss of radio bearers etc.) from stored data associated with a network (e.g. node details, traffic details etc.), and determines (330) one or more discriminating features (e.g. node type, network type, service type etc.) of the first subset of events using a feature selection method (e.g. mutual information, information gain, principal feature analysis etc.). The device also retrieves one or more additional stored subsets (350) of events, different than the first subset of events, from the data associated with the network, and cross-checks (310) for the presence of the discriminating feature(s) in the additional subset(s) of events. The device then detects (320) a feature that is a root cause of a problem in the network based on the cross-checked discriminating feature(s).
Abstract:
A device retrieves a first subset of events from data associated with a network, and determines one or more discriminating features of the first subset of events using a feature selection method. The device also retrieves one or more additional subsets o f events, different than the first subset of events, from the data associated with the network, and cross validates the one or more discriminating features based on the one or more additional subsets of events. The device further detects a feature that is a root cause of a problem in the network based on the cross validated one or more discriminating features.
Abstract:
A device retrieves a first subset of events from data associated with a network, and determines one or more discriminating features of the first subset of events using a feature selection method. The device also retrieves one or more additional subsets of events, different than the first subset of events, from the data associated with the network, and cross validates the one or more discriminating features based on the one or more additional subsets of events. The device further detects a feature that is a root cause of a problem in the network based on the cross validated one or more discriminating features.