Abstract: In one general aspect, a system and method are described for generating a classification model to determine predictive user behavior. The method may include obtaining data from a mobile network provider. The data including a plurality of utilization metrics pertaining to a plurality of mobile devices carrying out a plurality of network interactions, the plurality of mobile devices being associated with a plurality of users. The method may also include categorizing the data into a plurality of Internet domains associated with the data and determining a plurality of patterns in the data. The method may further include determining an additional pattern in the data, and generating a plurality of rules based on the plurality of patterns and the additional pattern.

Abstract: In one general aspect, a system and method are described for generating a classification model to determine predictive user behavior. The method may include obtaining data from a mobile network provider. The data including a plurality of utilization metrics pertaining to a plurality of mobile devices carrying out a plurality of network interactions, the plurality of mobile devices being associated with a plurality of users. The method may also include categorizing the data into a plurality of Internet domains associated with the data and determining a plurality of patterns in the data. The method may further include determining an additional pattern in the data, and generating a plurality of rules based on the plurality of patterns and the additional pattern.

Abstract: In one general aspect, a system and method are described for generating a classification model to determine predictive user behavior. The method may include obtaining data from a mobile network provider. The data including a plurality of utilization metrics pertaining to a plurality of mobile devices carrying out a plurality of network interactions, the plurality of mobile devices being associated with a plurality of users. The method may also include categorizing the data into a plurality of Internet domains associated with the data and determining a plurality of patterns in the data. The method may further include determining an additional pattern in the data, and generating a plurality of rules based on the plurality of patterns and the additional pattern.

Abstract: In one general aspect, a system and method are described for generating a classification model to determine predictive user behavior. The method may include obtaining data from a mobile network provider. The data including a plurality of utilization metrics pertaining to a plurality of mobile devices carrying out a plurality of network interactions, the plurality of mobile devices being associated with a plurality of users. The method may also include categorizing the data into a plurality of Internet domains associated with the data and determining a plurality of patterns in the data. The method may further include determining an additional pattern in the data, and generating a plurality of rules based on the plurality of patterns and the additional pattern.

Abstract: A method and corresponding apparatus configured to collect raw data from a plurality of wireless devices. The raw data includes activity recorded when the wireless devices are at a selected topographic region. The raw data is combined to produce aggregated data representative of the activities of the individual wireless devices. Either the aggregated data or the raw data are selected for analysis depending on whether the raw data meets a threshold activity or subscriber density level. The selected data are analyzed to identify activity patterns of users of the wireless devices.

Abstract: A method and corresponding apparatus configured to collect raw data from a plurality of wireless devices. The raw data includes activity recorded when the wireless devices are at a selected topographic region. The raw data is combined to produce aggregated data representative of the activities of the individual wireless devices. Either the aggregated data or the raw data are selected for analysis depending on whether the raw data meets a threshold activity or subscriber density level. The selected data are analyzed to identify activity patterns of users of the wireless devices.

Abstract: A method and corresponding apparatus that is configured to receive data from a data producer (such as for example a telecommunications provider like a mobile operator); process (e.g., analyze, aggregate, etc.) the received data; and supply aspects of the results of the processing to a data consumer through for example an array of user interfaces.