Conviva Inc.

Primer Technologies, Inc.

Oleg Vasilyev

Aditya Ravikumar Ganjam

Jibin Zhan

Faisal Zakaria Siddiqi

Alexey Serbin

Davis Shepherd

Henry Milner

John Bohannon

Wensi Fu

Thomas Alexander Grek

Sandeep Pombra

The technology disclosed herein summarizes a document using a dictionary derived from tokens within the document itself. In a particular implementation, a method provides identifying a first document for summarization and inputting the first document into a natural language model. The natural language model is configured to summarize the first document using words from a first dictionary compiled based on tokens from the first document. The method further provides receiving a first summary output by the natural language model after the natural language model summarizes the first document.

Limiting a dictionary used by a natural language model to summarize a document

Selecting an optimal bitrate range is disclosed. A request for content from a first client is received. An optimal subset of bitrates for the first client is determined. The optimal subset of bitrates for the first client is determined based at least in part on one or more real-time quality measures. A different optimal subset of bitrates is determined for a second client. An indication of the optimal subset of bitrates determined for the first client is provided to the first client. The first client is configured to obtain content according to the indication of the optimal subset of bitrates.

Dynamic bitrate range selection in the cloud for optimized video streaming

Fault isolation in over-the-top content (OTT) broadband networks is disclosed. Network topology information associated with a network service provider is received. Session information associated with one or more streaming sessions is received. A predictive model is generated for predicting session quality at least in part by using at least some of the network topology and session summary information as features. The predictive model is used to determine a first prediction of session quality using a first set of feature values. A second set of feature values is generated at least in part by replacing a first feature value in the first set of feature values with a replacement value. The predictive model is used to determine a replacement prediction of session quality using the second set of feature values including the replacement value with which the first feature value was replaced. Based at least in part on the first prediction and the replacement prediction, an impact of the first feature value on session quality is determined. A fault in a content delivery ecosystem is isolated based at least in part on the determined impact of the first feature value on session quality.

Fault isolation in over-the-top content (OTT) broadband networks

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Palo Alto, CA, United States of America

Oleg Vasilyev