公开(公告)号：US11176181B2

公开(公告)日：2021-11-16

申请号：US16594813

申请日：2019-10-07

Applicant: Google LLC

Inventor： Sushrut Suresh Karanjkar ,  Viswanath Subramanian ,  Shashidhar Anil Thakur

IPC: G06F16/29 ,  G06F16/9537 ,  G06F16/2457

Abstract: A server system associates one or more locations with a query by identifying the query, selecting a set of documents responsive to the query, and assigning weights to respective documents in the set of documents based, at least in part, on historical data of user clicks selecting search result links in search results produced for historical queries substantially the same as the identified query. Websites hosting the selected documents are identified, and, for each website, location-specific information for one or more locations is retrieved, including a location-specific score that corresponds to the likelihood that the respective location corresponds to a respective website. For each respective location for which location-specific information was retrieved, aggregating the location-specific scores, as weighted by the document weights, to compute an aggregated likelihood that the respective location is associated with the query. A specific location is assigned to the query when predefined criteria are satisfied.

公开(公告)号：US11782998B2

公开(公告)日：2023-10-10

申请号：US17277820

申请日：2020-02-28

Applicant: Google LLC

Inventor： Suddha Kalyan Basu ,  Wei Fan ,  Daniel Glasner ,  Sushrut Suresh Karanjkar ,  Thomas Richard Strohmann ,  Shubhang Verma ,  Manas Ashok Pathak ,  Wenyuan Yin ,  Sundeep Tirumalareddy

IPC: G06F16/50 ,  G06N3/02 ,  G06F16/9538 ,  G06F16/583 ,  G06F16/538 ,  G06F16/587 ,  G06F16/90 ,  G06N3/04 ,  G06N3/08

CPC classification number: G06F16/9538 ,  G06F16/538 ,  G06F16/583 ,  G06F16/587 ,  G06N3/02

Abstract: Methods, systems, and apparatus including computer programs encoded on a computer storage medium, for retrieving image search results using embedding neural network models. In one aspect, an image search query is received. A respective pair numeric embedding for each of a plurality of image-landing page pairs is determined. Each pair numeric embedding is a numeric representation in an embedding space. An image search query embedding neural network processes features of the image search query and generates a query numeric embedding. The query numeric embedding is a numeric representation of the image search query in the same embedding space. A subset of the image-landing page pairs having pair numeric embeddings that are closest to the query numeric embedding of the image search query in the embedding space are identified as first candidate image search results.

公开(公告)号：US20200034378A1

公开(公告)日：2020-01-30

申请号：US16594813

申请日：2019-10-07

Applicant: Google LLC

Inventor： Sushrut Suresh Karanjkar ,  Viswanath Subramanian ,  Shashidhar Anil Thakur

IPC: G06F16/29 ,  G06F16/9537 ,  G06F16/2457

Abstract: A server system associates one or more locations with a query by identifying the query, selecting a set of documents responsive to the query, and assigning weights to respective documents in the set of documents based, at least in part, on historical data of user clicks selecting search result links in search results produced for historical queries substantially the same as the identified query. Websites hosting the selected documents are identified, and, for each website, location-specific information for one or more locations is retrieved, including a location-specific score that corresponds to the likelihood that the respective location corresponds to a respective website. For each respective location for which location-specific information was retrieved, aggregating the location-specific scores, as weighted by the document weights, to compute an aggregated likelihood that the respective location is associated with the query. A specific location is assigned to the query when predefined criteria are satisfied.

公开(公告)号：US12086198B2

公开(公告)日：2024-09-10

申请号：US18461049

申请日：2023-09-05

Applicant: Google LLC

Inventor： Suddha Kalyan Basu ,  Wei Fan ,  Daniel Glasner ,  Sushrut Suresh Karanjkar ,  Thomas Richard Strohmann ,  Shubhang Verma ,  Manas Ashok Pathak ,  Wenyuan Yin ,  Sundeep Tirumalareddy

IPC: G06F16/50 ,  G06F16/538 ,  G06F16/583 ,  G06F16/587 ,  G06F16/9538 ,  G06N3/02 ,  G06F16/90

CPC classification number: G06F16/9538 ,  G06F16/538 ,  G06F16/583 ,  G06F16/587 ,  G06N3/02

Abstract: Methods, systems, and apparatus including computer programs encoded on a computer storage medium, for retrieving image search results using embedding neural network models. In one aspect, an image search query is received. A respective pair numeric embedding for each of a plurality of image-landing page pairs is determined. Each pair numeric embedding is a numeric representation in an embedding space. An image search query embedding neural network processes features of the image search query and generates a query numeric embedding. The query numeric embedding is a numeric representation of the image search query in the same embedding space. A subset of the image-landing page pairs having pair numeric embeddings that are closest to the query numeric embedding of the image search query in the embedding space are identified as first candidate image search results.

公开(公告)号：US20240394319A1

公开(公告)日：2024-11-28

申请号：US18798316

申请日：2024-08-08

Applicant: Google LLC

Inventor： Suddha Kalyan Basu ,  Wei Fan ,  Daniel Glasner ,  Sushrut Suresh Karanjkar ,  Thomas Richard Strohmann ,  Shubhang Verma ,  Manas Ashok Pathak ,  Wenyuan Yin ,  Sundeep Tirumalareddy

IPC: G06F16/9538 ,  G06F16/538 ,  G06F16/583 ,  G06F16/587 ,  G06N3/02

Abstract: Methods, systems, and apparatus including computer programs encoded on a computer storage medium, for retrieving image search results using embedding neural network models. In one aspect, an image search query is received. A respective pair numeric embedding for each of a plurality of image-landing page pairs is determined. Each pair numeric embedding is a numeric representation in an embedding space. An image search query embedding neural network processes features of the image search query and generates a query numeric embedding. The query numeric embedding is a numeric representation of the image search query in the same embedding space. A subset of the image-landing page pairs having pair numeric embeddings that are closest to the query numeric embedding of the image search query in the embedding space are identified as first candidate image search results.

公开(公告)号：US20230409653A1

公开(公告)日：2023-12-21

申请号：US18461049

申请日：2023-09-05

Applicant: Google LLC

Inventor： Suddha Kalyan Basu ,  Wei Fan ,  Daniel Glasner ,  Sushrut Suresh Karanjkar ,  Thomas Richard Strohmann ,  Shubhang Verma ,  Manas Ashok Pathak ,  Wenyuan Yin ,  Sundeep Tirumalareddy

IPC: G06F16/9538 ,  G06F16/583 ,  G06F16/538 ,  G06F16/587 ,  G06N3/02

CPC classification number: G06F16/9538 ,  G06F16/583 ,  G06F16/538 ,  G06F16/587 ,  G06N3/02

Abstract: Methods, systems, and apparatus including computer programs encoded on a computer storage medium, for retrieving image search results using embedding neural network models. In one aspect, an image search query is received. A respective pair numeric embedding for each of a plurality of image-landing page pairs is determined. Each pair numeric embedding is a numeric representation in an embedding space. An image search query embedding neural network processes features of the image search query and generates a query numeric embedding. The query numeric embedding is a numeric representation of the image search query in the same embedding space. A subset of the image-landing page pairs having pair numeric embeddings that are closest to the query numeric embedding of the image search query in the embedding space are identified as first candidate image search results.