Samsung Electronics Co., Ltd.

Google Inc.

Rui Chen

Shishir Samir Mehrotra

Armand Joseph Dijamco

Jeffrey Lee-Chan

Aaron Kwong Yue Lee

Shenaz Zack

Yannet Interian

Jianliang Zhao

Chetan Hari Narain

Lin Shi

Li Li

Hongxia Jin

Yong Ge

Yilin Shen

Shiva Prasad Kasiviswanathan

Soo-Hyun Choi

Haoran Li

Xianshan Qu

Xi Liu

Ninghao Liu

Xia Hu

A method includes obtaining, by an electronic device, an interpretation hierarchy generated based on a knowledge graph and behavioral data. The method also includes performing, by the electronic device, graph convolution operations on the interpretation hierarchy to generate one or more embeddings. The method further includes generating, by the electronic device, a recommendation based at least in part on associations between the one or more embeddings. In addition, the method includes providing, by the electronic device, an explanation corresponding to the recommendation.

System and method for explainable embedding-based recommendation system

Media items to be hosted at an asset hosting platform and submitted by an owner of the media items are received. The media items are provided for consumption by users of the asset hosting platform. The historical data identifies a historical popularity of one or more of the media items. Whether the historical data associated with the one or more of the media items satisfies a viewership rate specifying a rate of viewership over a predetermined period of time for the one or more of the media items is determined. Responsive to determining that the historical data associated with the one or more of the media items satisfies the viewership rate, the owner is determined as eligible to participate in a performance sharing program. A communication for a client device associated with the owner of the media items to invite the owner to participate in the performance sharing program is generated.

Video revenue sharing program

Videos to be hosted at an asset hosting platform and submitted by an owner of the videos are received. The videos are provided for consumption by users of the asset hosting platform. The historical data identifies a historical popularity of one or more of the videos. Whether the historical data associated with the one or more of the videos satisfies a viewership rate specifying a rate of viewership over a predetermined period of time for the one or more of the videos is determined. Responsive to determining that the historical data associated with the one or more of the videos satisfies the viewership rate, the owner is determined as eligible to participate in a video performance sharing program. A communication for a client device associated with the owner of the videos to invite the owner to participate in the video performance sharing program is generated.

A system and method capable of learning dynamic user and advertisement behavior for more effective click-through rate prediction. The system and method include at least one processor configured to obtain at least one item data, wherein the at least one item data comprises at least one explicit feedback to a user interaction event and other data associated with an item. The at least one processor also uses an interaction model that incorporates the obtained at least one item data to generate a user response prediction for a user and another interaction event.

System and method for click-through rate prediction

A system and method generates a popularity score for a first video based at least in part on first popularity data. The popularity score indicative of a popularity of the first video. The system and method retrieves first historical data including historical popularity of a second video submitted by an owner of the first video, in view of determining that the popularity score for the first video is greater than a predetermined value. The system and method determines that the second video is eligible to participate in a video performance sharing program based at least in part on the first historical data. The system and method generates a communication for a client device associated with the owner of the second video to invite the owner of the second video to participate in the video performance sharing program.

A first device specifies a privacy specification. The privacy specification includes at least a safe zone and a precision parameter may also be specified. A second device, such as an untrusted server, uses the privacy specification to provide guidance to the first device on how to perturb sensitive data. The first device then uses the guidance to transform sensitive data and provides it to the second device. The data transformation permits the first device to share sensitive data in a manner that preserves the privacy of the first user but permits statistics on aggregated data to be generated by an untrusted server.

Private dataaggregation framework for untrusted servers

An apparatus, method, and computer readable medium for management of infinite data streams. The apparatus includes a memory that stores streaming data with a data set and a processor operably connected to the memory. The processor transforms the data set to a second data set. To transform the data set, the processor determines whether a difference level exceeds a threshold, and transforms the data set by adding a noise when the difference level exceeds the threshold. When the difference level does not exceed the threshold, the processor determines whether a retroactive count is greater than a threshold, transforms the data set by adding a second noise when the retroactive count is greater than the threshold, and transforms the data set by adding a third noise when the retroactive count is not greater than the threshold. The processor transmits the second data set to a data processing system for further processing.

System and method for privacy management of infinite data streams

A system and method for sharing revenue associated with a video is disclosed. The method includes generating a popularity score for a first video based at least in part on first popularity data. The popularity score is indicative of present and future popularity of the first video. The method also includes retrieving historical data includes historical popularity and profitability of multiple videos submitted by an owner of the first video, in response to determining that the popularity score for the first video is greater than a predetermined value. The method also includes determining that the first video is eligible to participate in a revenue sharing program based at least in part on the retrieved historical data. The method includes generating a message for a client device associated with the owner of the first video to invite the owner of the first video to participate in the revenue sharing program.

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San Jose, CA, United States of America

Rui Chen