Sling Media Inc.

Dish Wireless L.l.c.

Sling Media Pvt. Ltd.

Kalleri Faizel Rehiman

David Randolph Eyler

Satish Nayak

Yongjoon Oh

Madhukar Pulluru

Gurubasappa Kore

Ravinder Chouhan

Qi Chu

Mikhail L Arbuzov

Sisong Bei

Christine Chu

Dmitry Dimov

Chih Jen Ken Lee

Davide Girlando

Sooraj Raveendran

The system obtains a first low-level information representing a first multiplicity of activities. The first low-level information includes a first log including a first multiplicity of entries representing the first activity. An entry among the first multiplicity of entries can represent various activities. The system obtains a second low-level information representing a second multiplicity of activities. The second low-level information includes a second log comprising a second multiplicity of entries. The system obtains a correspondence between the second multiplicity of activities and the second low-level information. The correspondence maps a second activity among the second multiplicity of activities to a subset of entries in the second log. The system determines that the subset of entries in the second log and a subset of entries in the first log are similar and the subset of entries in the first log indicates the second activity.

Determining an activity associated with a mobile device based on a low-level information representing the activity

The system obtains data associated with UE, representing interaction between the UE and a network. The data includes: previous bandwidth usage associated with the UE, previous CDR associated with the UE, anticipated geolocation of the UE, a plan associated with the UE, one or more media events, a number of lines associated with the UE, a length of time the UE has been associated with the network, and a unique identifier associated with the UE. The system obtains multiple plans associated with the network, where a plan indicates the bandwidth usage associated with the UE within a predetermined period. Based on the data, the system predicts the bandwidth usage associated with the UE within the predetermined period to obtain a predicted bandwidth usage and determines the plan among the multiple plans accommodating the predicted bandwidth usage. The system requests the bandwidth usage associated with the plan from the network.

Predicting a bandwidth usage associated with a mobile device operating on a wireless telecommunication network

Multimedia systems and related methods and devices are provided for recommending media programs to a user. Viewing characteristics of the user are determined based on usage information detailing preceding viewing sessions for the user. In one or more embodiments, the user's current interest in one or more currently available media programs that originated after the user's preceding viewing session is predicted based on the user's viewing characteristics and the current viewing context, and media programs having the highest predicted current interest are indicated to the user as being recommended.

Media systems for temporally and contextually relevant recommendations

A method of providing data associated with reception of media content is presented. In the method, a communication device receives media content from a media content receiver via a communication network. The received media content is output to a user of the communication device. Data is then generated in the communication device which includes information identifying a channel selected by the user over which the media content receiver receives the media content. The data further includes information identifying a time period during which the communication device receives the media content. The data is transferred via the communication network to a communication node.

Generation of data concerning reception of media content at a communication device

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Fremont, CA, United States of America

Kalleri Faizel Rehiman