公开(公告)号：US20240078258A1

公开(公告)日：2024-03-07

申请号：US18505776

申请日：2023-11-09

Applicant: Google LLC

Inventor： Zhen Li ,  Yi-ting Chen ,  Ning Ye ,  Yaxi Gao ,  Zijian Guo ,  Aleksei Timofeev ,  Futang Peng ,  Thomas J. Duerig

IPC: G06F16/55 ,  G06F16/242 ,  G06F16/953 ,  G06F18/22 ,  G06N3/044 ,  G06N3/084 ,  G06N20/00

CPC classification number: G06F16/55 ,  G06F16/2425 ,  G06F16/953 ,  G06F18/22 ,  G06N3/044 ,  G06N3/084 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an image embedding model and a text embedding model. In one aspect, a method comprises: processing data from a historical query log of a search system to generate a candidate set of training examples, wherein each training example comprises: (i) a search query comprising a sequence of one or more words, (ii) an image, and (iii) selection data characterizing how often users selected the image in response to the image being identified by a search result for the search query; selecting a plurality of training examples from the candidate set of training examples; and using the training data to jointly train the image embedding model and the text embedding model.

公开(公告)号：US20200250538A1

公开(公告)日：2020-08-06

申请号：US16265811

申请日：2019-02-01

Applicant: Google LLC

Inventor： Zhen Li ,  Yi-ting Chen ,  Ning Ye ,  Yaxi Gao ,  Zijian Guo ,  Aleksei Timofeev ,  Futang Peng ,  Thomas J. Duerig

IPC: G06N3/08 ,  G06K9/62 ,  G06F16/953 ,  G06F16/242 ,  G06N20/00 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an image embedding model and a text embedding model. In one aspect, a method comprises: processing data from a historical query log of a search system to generate a candidate set of training examples, wherein each training example comprises: (i) a search query comprising a sequence of one or more words, (ii) an image, and (iii) selection data characterizing how often users selected the image in response to the image being identified by a search result for the search query; selecting a plurality of training examples from the candidate set of training examples; and using the training data to jointly train the image embedding model and the text embedding model.

公开(公告)号：US11586927B2

公开(公告)日：2023-02-21

申请号：US16265793

申请日：2019-02-01

Applicant: Google LLC

Inventor： Zhen Li ,  Yi-ting Chen ,  Yaxi Gao ,  Da-Cheng Juan ,  Aleksei Timofeev ,  Chun-Ta Lu ,  Futang Peng ,  Sujith Ravi ,  Andrew Tomkins ,  Thomas J. Duerig

IPC: G06K9/00 ,  G06N3/084 ,  G06F16/538 ,  G06F16/9538 ,  G06K9/62 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image embedding model. In one aspect, a method comprises: obtaining training data comprising a plurality of training examples, wherein each training example comprises: an image pair comprising a first image and a second image; and selection data indicating one or more of: (i) a co-click rate of the image pair, and (ii) a similar-image click rate of the image pair; and using the training data to train an image embedding model having a plurality of image embedding model parameters.

公开(公告)号：US20200250537A1

公开(公告)日：2020-08-06

申请号：US16265793

申请日：2019-02-01

Applicant: Google LLC

Inventor： Zhen Li ,  Yi-ting Chen ,  Yaxi Gao ,  Da-Cheng Juan ,  Aleksei Timofeev ,  Chun-Ta Lu ,  Futang Peng ,  Sujith Ravi ,  Andrew Tomkins ,  Thomas J. Duerig

IPC: G06N3/08 ,  G06K9/62 ,  G06F16/9538 ,  G06F16/538 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for training an image embedding model. In one aspect, a method comprises: obtaining training data comprising a plurality of training examples, wherein each training example comprises: an image pair comprising a first image and a second image; and selection data indicating one or more of: (i) a co-click rate of the image pair, and (ii) a similar-image click rate of the image pair; and using the training data to train an image embedding model having a plurality of image embedding model parameters.