Abstract:
The present disclosure relates generally to methods for characterizing communication networks, and more particularly to methods of characterizing the propagation of information throughout communications in such networks.
Abstract:
The present utility model discloses a rotatable adjusting cleaner, comprising a brush head mounting handle, a rotational handle rotatably connected to the brush head mounting handle, and a rotational adjusting mechanism provided between the brush head mounting handle and the rotational handle; by providing a rotational adjusting mechanism between the brush head mounting handle and the rotational handle, the present utility model can achieve the rotatable adjustment of the two, so as to facilitate a user to adjust the angle of the brush head according to cleaning requirements, thereby enhancing the convenience of the use of the present application
Abstract:
A community mining system analyzes objects of different types and relationships between the objects of different types to identify communities. The relationships between the objects have an associated time. The community mining system extracts various features related to objects of a designated type from the relationships between objects of different types that represent the evolution of the features over time. The community mining system collects training data that indicates extracted features associated with members of the communities. The community mining system then classifies an object of the designated type as being within the community based on closeness of the features of the object to the features of the training data.
Abstract:
The present disclosure relates generally to methods for characterizing communication networks, and more particularly to methods of characterizing the propagation of information throughout communications in such networks.
Abstract:
A community mining system analyzes objects of different types and relationships between the objects of different types to identify communities. The relationships between the objects have an associated time. The community mining system extracts various features related to objects of a designated type from the relationships between objects of different types that represent the evolution of the features over time. The community mining system collects training data that indicates extracted features associated with members of the communities. The community mining system then classifies an object of the designated type as being within the community based on closeness of the features of the object to the features of the training data.