Patents by Inventor Andrew Huan Zhai
Andrew Huan Zhai has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240061875Abstract: Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.Type: ApplicationFiled: November 2, 2023Publication date: February 22, 2024Applicant: Pinterest, Inc.Inventors: Nikil Pancha, Andrew Huan Zhai, Charles Joseph Rosenberg
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Patent number: 11841897Abstract: Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.Type: GrantFiled: December 29, 2022Date of Patent: December 12, 2023Assignee: Pinterest, Inc.Inventors: Nikil Pancha, Andrew Huan Zhai, Charles Joseph Rosenberg
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Patent number: 11841735Abstract: Described is a system and method for enabling visual search for information. With each selection of an object included in an image, additional images that include visually similar objects are determined and presented to the user.Type: GrantFiled: September 22, 2017Date of Patent: December 12, 2023Assignee: Pinterest, Inc.Inventors: Andrew Huan Zhai, Zhiyuan Zhang, Kevin Yushi Jing, Dmitry Olegovich Kislyuk
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Publication number: 20230252550Abstract: Described are systems and methods for providing a multi-tasked trained machine learning model that may be configured to generate product embeddings from multiple types of product information. The exemplary product embeddings may be generated for a corpus of products (e.g., products included in a product catalog, etc.) based on both image information and text information associated with each respective product. Accordingly, the generated product embeddings may be compatible with learned representations of the different types of product information (e.g., image information, text information, etc.) and may be used to create a product index, which can be used to determine and serve product recommendations in connection with multiple different recommendation services that may be configured to receive different types of inputs (e.g., a single image, multiple images, text-based information, etc.).Type: ApplicationFiled: February 9, 2023Publication date: August 10, 2023Applicant: Pinterest, Inc.Inventors: Paul Baltescu, Andrew Huan Zhai, Haoyu Chen, Jurij Leskovec, Nikil Pancha, Charles Joseph Rosenberg
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Publication number: 20230252269Abstract: Described are systems and methods for providing a sequential trained machine learning model that may be configured to generate a user embedding that is representative of the user and is configured to predict a plurality of the user's actions over a period of time. The exemplary sequential trained machine learning model may be employed, for example, in connection with recommendation, search, and/or other services. Exemplary embodiments of the present disclosure may also employ the user embeddings generated by the exemplary sequential trained machine learning model in connection with one or more conditional retrieval systems that may include an end-to-end learned model, which are configured to generate updated user embeddings based on the user embeddings generated by the exemplary sequential trained machine learning model and certain contextual information.Type: ApplicationFiled: February 8, 2023Publication date: August 10, 2023Applicant: Pinterest, Inc.Inventors: Andrew Huan Zhai, Nikil Pancha, Haoyu Chen, Kofi Boakye
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Publication number: 20230229695Abstract: Described is a system and method for enabling dynamic selection of a search input. For example, rather than having a static search input box, the search input may be dynamically positioned such that it encompasses a portion of displayed information. An image segment that includes a representation of the encompassed portion of the displayed information is generated and processed to determine an object represented in the portion of the displayed information. Additional images with visually similar representations of objects are then determined and presented to the user.Type: ApplicationFiled: March 17, 2023Publication date: July 20, 2023Applicant: Pinterest, Inc.Inventors: Kelei Xu, Naveen Gavini, Yushi Jing, Andrew Huan Zhai, Dmitry Olegovich Kislyuk
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Publication number: 20230185840Abstract: Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.Type: ApplicationFiled: December 29, 2022Publication date: June 15, 2023Applicant: Pinterest, Inc.Inventors: Nikil Pancha, Andrew Huan Zhai, Charles Joseph Rosenberg
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Publication number: 20230177089Abstract: Systems and methods for identifying content for an input query are presented. A mapping model is trained to map elements of an input query embedding vector for a received query into one or more elements of a destination embedding vector. In response to receiving an input query, an input query embedding vector is generated that projects into an input query embedding space. The input query embedding vector is processed by the mapping model to map the input query embedding vector into one or more elements of a destination embedding vector in a destination embedding space, resulting in a partial destination embedding vector. Items of a corpus of content are projected into the destination embedding space and the partial destination embedding vector is also projected into the destination embedding space. A similarity measure determines the most-similar items to the partial destination embedding vector and at least some of the most-similar items are returned in response to the input query.Type: ApplicationFiled: February 2, 2023Publication date: June 8, 2023Applicant: Pinterest, Inc.Inventors: Andrew Huan Zhai, Kaifeng Chen, Charles Joseph Rosenberg
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Patent number: 11609946Abstract: Described is a system and method for enabling dynamic selection of a search input. For example, rather than having a static search input box, the search input may be dynamically positioned such that it encompasses a portion of displayed information. An image segment that includes a representation of the encompassed portion of the displayed information is generated and processed to determine an object represented in the portion of the displayed information. Additional images with visually similar representations of objects are then determined and presented to the user.Type: GrantFiled: October 5, 2015Date of Patent: March 21, 2023Assignee: Pinterest, Inc.Inventors: Kelei Xu, Naveen Gavini, Yushi Jing, Andrew Huan Zhai, Dmitry Olegovich Kislyuk
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Patent number: 11574020Abstract: Systems and methods for identifying content for an input query are presented. A mapping model is trained to map elements of an input query embedding vector for a received query into one or more elements of a destination embedding vector. In response to receiving an input query, an input query embedding vector is generated that projects into an input query embedding space. The input query embedding vector is processed by the mapping model to map the input query embedding vector into one or more elements of a destination embedding vector in a destination embedding space, resulting in a partial destination embedding vector. Items of a corpus of content are projected into the destination embedding space and the partial destination embedding vector is also projected into the destination embedding space. A similarity measure determines the most-similar items to the partial destination embedding vector and at least some of the most-similar items are returned in response to the input query.Type: GrantFiled: December 12, 2019Date of Patent: February 7, 2023Assignee: Pinterest, Inc.Inventors: Andrew Huan Zhai, Kaifeng Chen, Charles Joseph Rosenberg
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Patent number: 11544317Abstract: Systems and methods for responding to a subscriber's text-based request for content items are presented. In response to a request from a subscriber, word pieces are generated from the text-based terms of the request. A request embedding vector of the word pieces is obtained from a trained machine learning model. Using the request embedding vector, a set of content items, from a corpus of content items, is identified. At least some content items of the set of content items are returned to the subscriber in response to the text-based request for content items.Type: GrantFiled: August 20, 2020Date of Patent: January 3, 2023Assignee: Pinterest, Inc.Inventors: Nikil Pancha, Andrew Huan Zhai, Charles Joseph Rosenberg
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Publication number: 20210382934Abstract: Described is a system and method for enabling dynamic selection of a search input. For example, rather than having a static search input box, the search input may be dynamically positioned such that it encompasses a portion of displayed information. For example, a user may touch a touch-based display using two fingers to invoke the dynamic search input and then determine a size and a position of the dynamic search input by moving their fingers on the display. An image segment that includes a representation of the encompassed portion of the displayed information is generated and processed to determine an object represented in the portion of the displayed information. Additional images with visually similar representations of objects are then determined and presented to the user.Type: ApplicationFiled: July 2, 2021Publication date: December 9, 2021Inventors: Kelei Xu, Naveen Gavini, Kevin Yushi Jing, Andrew Huan Zhai, Dmitry Olegovich Kislyuk, Adam Jay Barton, Marcelo Reis e Silva de Queiroz
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Patent number: 11126653Abstract: Described is a system and method for enabling visual search for information. With each selection of an object included in an image, additional images that include visually similar objects are determined and presented to the user.Type: GrantFiled: September 22, 2017Date of Patent: September 21, 2021Assignee: Pinterest, Inc.Inventors: Andrew Huan Zhai, Dmitry Olegovich Kislyuk, Maesen Churchill, Yue Li Du, Zhefei Yu, Kelei Xu
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Patent number: 11055343Abstract: Described is a system and method for enabling dynamic selection of a search input. For example, rather than having a static search input box, the search input may be dynamically positioned such that it encompasses a portion of displayed information. For example, a user may touch a touch-based display using two fingers to invoke the dynamic search input and then determine a size and a position of the dynamic search input by moving their fingers on the display. An image segment that includes a representation of the encompassed portion of the displayed information is generated and processed to determine an object represented in the portion of the displayed information. Additional images with visually similar representations of objects are then determined and presented to the user.Type: GrantFiled: July 11, 2017Date of Patent: July 6, 2021Assignee: Pinterest, Inc.Inventors: Kelei Xu, Naveen Gavini, Kevin Yushi Jing, Andrew Huan Zhai, Dmitry Olegovich Kislyuk, Adam Jay Barton, Marcelo Reis e Silva de Queiroz
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Publication number: 20190095465Abstract: Described is a system and method for enabling visual search for information. With each selection of an object included in an image, additional images that include visually similar objects are determined and presented to the user.Type: ApplicationFiled: September 22, 2017Publication date: March 28, 2019Inventors: Andrew Huan Zhai, Zhiyuan Zhang, Kevin Yushi Jing, Dmitry Olegovich Kislyuk
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Publication number: 20190095466Abstract: Described is a system and method for enabling visual search for information. With each selection of an object included in an image, additional images that include visually similar objects are determined and presented to the user.Type: ApplicationFiled: September 22, 2017Publication date: March 28, 2019Inventors: Andrew Huan Zhai, Dmitry Olegovich Kislyuk, Maesen Churchill, Yue Li Du, Zhefei Yu, Kelei Xu
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Publication number: 20170308553Abstract: Described is a system and method for enabling dynamic selection of a search input. For example, rather than having a static search input box, the search input may be dynamically positioned such that it encompasses a portion of displayed information. For example, a user may touch a touch-based display using two fingers to invoke the dynamic search input and then determine a size and a position of the dynamic search input by moving their fingers on the display. An image segment that includes a representation of the encompassed portion of the displayed information is generated and processed to determine an object represented in the portion of the displayed information. Additional images with visually similar representations of objects are then determined and presented to the user.Type: ApplicationFiled: July 11, 2017Publication date: October 26, 2017Inventors: Kelei Xu, Naveen Gavini, Kevin Yushi Jing, Andrew Huan Zhai, Dmitry Olegovich Kislyuk, Adam Jay Barton, Marcelo Reis e Silva de Queiroz
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Publication number: 20170097945Abstract: Described is a system and method for enabling dynamic selection of a search input. For example, rather than having a static search input box, the search input may be dynamically positioned such that it encompasses a portion of displayed information. An image segment that includes a representation of the encompassed portion of the displayed information is generated and processed to determine an object represented in the portion of the displayed information. Additional images with visually similar representations of objects are then determined and presented to the user.Type: ApplicationFiled: October 5, 2015Publication date: April 6, 2017Inventors: Kelei Xu, Naveen Gavini, Yushi Jing, Andrew Huan Zhai, Dmitry Olegovich Kislyuk