公开(公告)号：US20170300814A1

公开(公告)日：2017-10-19

申请号：US15394668

申请日：2016-12-29

Applicant: Google Inc.

Inventor： Tal Shaked ,  Rohan Anil ,  Hrishikesh Balkrishna Aradhye ,  Mustafa Ispir ,  Glen Anderson ,  Wei Chai ,  Mehmet Levent Koc ,  Jeremiah Harmsen ,  Xiaobing Liu ,  Gregory Sean Corrado ,  Tushar Deepak Chandra ,  Heng-Tze Cheng

IPC: G06N3/08 ,  G06N3/04

CPC classification number: G06N3/08 ,  G06N3/0454 ,  G06N3/0472 ,  G06N3/084

Abstract: A system includes one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the computers to implement a combined machine learning model for processing an input including multiple features to generate a predicted output for the machine learning input. The combined model includes: a deep machine learning model configured to process the features to generate a deep model output; a wide machine learning model configured to process the features to generate a wide model output; and a combining layer configured to process the deep model output generated by the deep machine learning model and the wide model output generated by the wide machine learning model to generate the predicted output, in which the deep model and the wide model have been trained jointly on training data to generate the deep model output and the wide model output.

公开(公告)号：US09608917B1

公开(公告)日：2017-03-28

申请号：US14058749

申请日：2013-10-21

Applicant: Google Inc.

Inventor： Glen Anderson ,  Steven Padgett ,  Junlan Zhou ,  Uday Ramakrishna Naik ,  Alok Kumar ,  Amin Vahdat ,  Sushant Jain

IPC: H04L12/851 ,  H04L12/801

CPC classification number: H04L47/2441 ,  H04L47/10 ,  H04L47/24 ,  H04L47/72

Abstract: Systems and methods for achieving high utilization of a network link are provided. A first communication protocol can be selected for transmitting network flows of a first type. A first quality of service can be assigned to network flows of the first type. A second communication protocol can be selected for transmitting network flows of a second type. A second quality of service, lower than the first quality of service, can be assigned to network flows of the second type. A first percentage of available bandwidth can be allocated to the network flows of both the first and second types. The remaining bandwidth, plus a second percentage of available bandwidth, can be allocated to the network flows of the second type, such that the total allocated bandwidth exceeds the available bandwidth of the network link.

公开(公告)号：US09535897B2

公开(公告)日：2017-01-03

申请号：US14136111

申请日：2013-12-20

Applicant: Google Inc.

Inventor： Glen Anderson ,  Michael Schuster

IPC: G06F17/27 ,  G06F17/28 ,  G06N3/02 ,  G06Q30/06 ,  H04N21/466 ,  G06F17/30 ,  H04N21/442

CPC classification number: G06Q30/0255 ,  G06F17/276 ,  G06F17/277 ,  G06F17/28 ,  G06F17/3064 ,  G06F17/30864 ,  G06F17/30873 ,  G06N3/02 ,  G06N3/08 ,  G06Q30/0631 ,  H04N21/44222 ,  H04N21/4666 ,  H04N21/4668

Abstract: The present disclosure relates to applying techniques similar to those used in neural network language modeling systems to a content recommendation system. For example, by associating consumed media content to words of a language model, the system may provide content predictions based on an ordering. Thus, the systems and techniques described herein may produce enhanced prediction results for recommending content (e.g. word) in a given sequence of consumed content. In addition, the system may account for additional user actions by representing particular actions as punctuation in the language model.

Abstract translation: 本公开涉及将类似于神经网络语言建模系统中使用的技术应用于内容推荐系统。 例如，通过将消耗的媒体内容与语言模型的单词相关联，系统可以基于排序来提供内容预测。 因此，本文描述的系统和技术可以产生用于在给定的消费内容序列中推荐内容（例如，单词）的增强的预测结果。 此外，系统可以通过将特定动作表示为语言模型中的标点符号来解释额外的用户操作。

公开(公告)号：US09934515B1

公开(公告)日：2018-04-03

申请号：US15370247

申请日：2016-12-06

Applicant: Google Inc.

Inventor： Glen Anderson ,  Michael Schuster

IPC: G06F17/27 ,  G06Q30/02 ,  H04N21/466 ,  H04N21/442 ,  G06F17/30 ,  G06N3/08

CPC classification number: G06Q30/0255 ,  G06F17/276 ,  G06F17/277 ,  G06F17/28 ,  G06F17/3064 ,  G06F17/30864 ,  G06F17/30873 ,  G06N3/02 ,  G06N3/08 ,  G06Q30/0631 ,  H04N21/44222 ,  H04N21/4666 ,  H04N21/4668

Abstract: The present disclosure relates to applying techniques similar to those used in neural network language modeling systems to a content recommendation system. For example, by associating consumed media content to words of a language model, the system may provide content predictions based on an ordering. Thus, the systems and techniques described herein may produce enhanced prediction results for recommending content (e.g. word) in a given sequence of consumed content. In addition, the system may account for additional user actions by representing particular actions as punctuation in the language model.

公开(公告)号：US20150178265A1

公开(公告)日：2015-06-25

申请号：US14136111

申请日：2013-12-20

Applicant: Google Inc.

Inventor： Glen Anderson ,  Michael Schuster

IPC: G06F17/27 ,  G06F17/28

CPC classification number: G06Q30/0255 ,  G06F17/276 ,  G06F17/277 ,  G06F17/28 ,  G06F17/3064 ,  G06F17/30864 ,  G06F17/30873 ,  G06N3/02 ,  G06N3/08 ,  G06Q30/0631 ,  H04N21/44222 ,  H04N21/4666 ,  H04N21/4668

Abstract: The present disclosure relates to applying techniques similar to those used in neural network language modeling systems to a content recommendation system. For example, by associating consumed media content to words of a language model, the system may provide content predictions based on an ordering. Thus, the systems and techniques described herein may produce enhanced prediction results for recommending content (e.g. word) in a given sequence of consumed content. In addition, the system may account for additional user actions by representing particular actions as punctuation in the language model.

Abstract translation: 本公开涉及将类似于神经网络语言建模系统中使用的技术应用于内容推荐系统。 例如，通过将消耗的媒体内容与语言模型的单词相关联，系统可以基于排序来提供内容预测。 因此，本文描述的系统和技术可以产生用于在给定的消费内容序列中推荐内容（例如，单词）的增强的预测结果。 此外，系统可以通过将特定动作表示为语言模型中的标点符号来解释额外的用户操作。