At&t Intellectual Property I, L.p.

Lien K Tran

Ann Eileen Skudlark

Yu Jin

Emir Halepovic

Simon D Byers

Christopher Volinsky

Carlos Eduardo De Andrade

David John Poole

Eric Martin Zavesky

David Crawford Gibbon

Zhu Liu

Vijay Gopalakrishnan

Jeffrey Erman

Wen-Ling Hsu

Appavu Siva Prakasam

Abhinav Srivastava

Cynthia Cama

Sanjeev Misra

Prashanth Boddhireddy

Siva Kolachina

Nisha Shahul Hameed

Jenq-Chyuan Wang

A cloud based mobile internet protocol messaging spam defense. Short message service (SMS) messages are analyzed by a cloud based virtual machine to determine if should be considered potentially unwanted messages (e.g., spam). The cloud based virtual machine uses a user specific algorithm for determining if a message should be considered to be a potentially unwanted message. Messages that are determined to be potentially unwanted messages trigger a notification to be sent to a user device associated with the virtual machine. The notification requests confirmation from the user that the potentially unwanted message is an unwanted message. The user's response to a request for confirmation is then used to update an unwanted message database associated with the user and the user device.

Cloud-based spam detection

Aspects of the subject disclosure may include, for example, determining classes from a corpus based on topic modeling, data clustering and unsupervised learning. Labels are determined for each of the classes and trained models are generated for each of the classes by assignment of a plurality of textual documents to labels based on a highest number of matches. A raw textual document can be tokenized and stop words removed. A corresponding one of the trained models can be selected according to a class that is applicable to subject matter of the raw textual document. The processed document can be assigned to a target label based on a highest number of matches of words. Other embodiments are disclosed.

Method and apparatus for labeling data

Aspects of the subject disclosure may include, for example, a method that includes obtaining metadata from media content and consumed by network subscribers; determining for each network subscriber a consumer context associated with the media content; and determining a media consumption pattern for each network subscriber based on the metadata and the consumer context, thereby generating a plurality of media consumption patterns. The method further includes aggregating the media consumption patterns; determining, based on the aggregated media consumption patterns, a media consumption trend for the network subscribers; and correlating the media consumption trend with a profile including a current activity for a network subscriber of the plurality of network subscribers, thereby generating a recommendation for the network subscriber regarding new media content not previously consumed by the network subscriber. The method also includes communicating the recommendation to the network subscriber. Other embodiments are disclosed.

System for trend discovery and curation from content metadata and context

A more efficient over-the-air software push can be facilitated by leveraging a smart scheduling system for vehicles. The smart scheduling system can use location and network capacity data to prioritize over-the-air software pushes for vehicles. For instance, a vehicle, which is only operational during off-peak wireless network hours can receive a software push during the off-peak times because wireless network capacity is not an issue. However, vehicles, which are used primarily during heavy peak wireless network times can receive software in a prioritized manner based on location data, frequency of use, network capacity, etc.

Facilitation of efficient software downloads for vehicles

Software downloads to Internet of things (IoT) devices are facilitated over a constrained network. In one embodiment a method comprises monitoring, by a network device comprising a processor, data determined to have been sent to a device for transmission to the device via a radio access network device of a wireless communication network, and determining, by the network device, a type of traffic associated with the data. The method further includes based on a determination that the data comprises firmware and that the type of traffic is of a traffic priority that is lower than a defined traffic priority, applying, by the network device, a low priority transport protocol to the data, wherein the applying comprises associating protocol information with the data representative of the low priority transport protocol.

Facilitating software downloads to internet of things devices via a constrained network

System and method for cloud based IP mobile messaging spam detection and defense

Network traffic usage information for a set of registered devices is monitored, analyzed, and reported within a cellular service provider portion of a communications network. The network traffic usage information can relate to data traffic, voice traffic, and/or short message service traffic. Reporting the network traffic usage information is customizable such that parameters associated with the network traffic usage can be changed, depending on the parameters that are of current interest to an organization affiliated with the set of registered devices.

Management of group mobile device network traffic usage

A crowd-sourced mobile messaging spam detection and defense system includes an application running on a mobile device. The application uses an unwanted message detection algorithm to analyze and classify messages as potential unwanted messages. The potential unwanted messages are presented to a user for confirmation that the messages are unwanted messages. In response to confirmation, the mobile device transmits a notification to a virtual machine associated with the user. The virtual machine uses the notification to update the unwanted message detection algorithm which may then be transmitted to the mobile device. The virtual machine may also transmit the notification to a global virtual machine. The global virtual machine may use the notification to update a set of classification rules maintained by the global virtual machine and transmit the set of classification rules as necessary to the multiple virtual machines for use in updating the unwanted message detection algorithm.

System and method for crowd-sourcing mobile messaging spam detection and defense

Growing community of inventors

Chatham, NJ, United States of America

Lien K Tran