Patents Assigned to Pinterest, Inc.
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Publication number: 20240249315Abstract: Described are systems and methods for generating recommendation campaigns that optimize for both a desired short-term user behavior and a desired long-term user behavior. In comparison to existing techniques that focus on targeting advertisements or recommendations to specific individuals with a single goal of receiving an interaction with the advertisement from that individual (i.e., a desired short-term behavior), the disclosed implementations consider the long-term user behavior, such as increased visits to a website during a long-term rage, and generate a recommendation campaign that also optimizes for that desired long-term user behavior.Type: ApplicationFiled: April 3, 2024Publication date: July 25, 2024Applicant: Pinterest, Inc.Inventors: Bo Zhao, John William Gupta Egan, Burkay Birant Orten, Koichiro Narita, Samuel Seth Weisfeld-Filson
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Patent number: 12038961Abstract: Systems and methods for determining one or more topics that may be associated and/or grounded with a node of a taxonomy to facilitate the creation and/or modification of the taxonomy. The one or more topics can be determined by generating two layers of associations and/or groundings. In a first layer, tokens can be associated and/or grounded in a corpus of queries, and in a second layer, topics can be associated and/or grounded in the tokens. The topics can then be associated with and/or grounded in nodes of a taxonomy which can facilitate access to content items stored and maintained by an online service. Further, in exemplary implementations where the content items include associations and/or mappings to the corpus of queries, the nodes of the taxonomy (which are associated with one or more topics) can be transitively mapped to the content items.Type: GrantFiled: June 20, 2022Date of Patent: July 16, 2024Assignee: Pinterest, Inc.Inventors: Abhijit Mahabal, Rui Huang
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Publication number: 20240223824Abstract: Described are systems and methods for determining and/or generating a queue of content items to improve the playback experience of the content items for a user. The content items may be obtained by a client device from an online service in response to a query, a request for content items, etc. Relevance rankings and/or scores associated with the content items may be replaced and/or augmented with a playability score, which can represent a quality of the playback experience associated with the content item. The playability score may be aggregated with the relevance and/or user engagement score to determine an overall playback score for each content item. The content items may be ranked, ordered, arranged, and/or presented in accordance with the overall playback scores associated with the content items to facilitate an improved playback experience for a user associated with the client device.Type: ApplicationFiled: March 14, 2024Publication date: July 4, 2024Applicant: Pinterest, Inc.Inventor: Liang Ma
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Publication number: 20240211698Abstract: Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.Type: ApplicationFiled: March 4, 2024Publication date: June 27, 2024Applicant: Pinterest, Inc.Inventors: Heath Vinicombe, Chenyi Li, Yunsong Guo, Yu Liu
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Patent number: 12001490Abstract: A method of determining relevancies of objects to a search query includes associating multiple tags with multiple objects, recording bookmarks to the multiple objects, or both, and determining a relevance score for each of the multiple objects and a search query. One embodiment of the method combines full-text relevance algorithms with tag relevance algorithms. Other embodiments include statistical relevance algorithms such as statistical classification or rank regression algorithms. When a user executes a search query, a results list containing the objects is returned, with the objects organized based on the relevance scores. The objects are organized by, for example, listing those with the highest relevance scores first or by marking them with an indication of their relevance.Type: GrantFiled: June 15, 2020Date of Patent: June 4, 2024Assignee: Pinterest, Inc.Inventors: Yunshan Lu, Michael Tanne
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Patent number: 11995142Abstract: Described are systems and methods that solve localization problems using Machine Learning models to compute country vectors for each linked content item and present content items in response to requests based on the country vectors. For example, a request from a user in Country A may be processed to determine candidate content items responsive to the request and to determine Country A as the country corresponding to the request. The candidate content items may then be processed to determine, for each candidate content item, a country vector corresponding to Country A as indicative of the relevance of the content item to Country A. Content items that are more likely than not to be relevant to the country of the request (e.g., Country A), as indicated by the respective country vector, may be considered as responsive and all other candidate content items discarded.Type: GrantFiled: August 16, 2021Date of Patent: May 28, 2024Assignee: Pinterest, Inc.Inventors: Fei Liu, Jun Liu, Siyang Xie, Yang Xiao
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Patent number: 11983735Abstract: Described are systems and methods for generating recommendation campaigns that optimize for both a desired short-term user behavior and a desired long-term user behavior. In comparison to existing techniques that focus on targeting advertisements or recommendations to specific individuals with a single goal of receiving an interaction with the advertisement from that individual (i.e., a desired short-term behavior), the disclosed implementations consider the long-term user behavior, such as increased visits to a website during a long-term rage, and generate a recommendation campaign that also optimizes for that desired long-term user behavior.Type: GrantFiled: June 2, 2017Date of Patent: May 14, 2024Assignee: Pinterest, Inc.Inventors: Bo Zhao, John William Gupta Egan, Burkay Birant Orten, Koichiro Narita, Samuel Seth Weisfeld-Filson
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Patent number: 11985253Abstract: Disclosed are systems and methods that authenticate non-fungible tokens (“NFT”) and/or digital data represented by or pointed to by an NFT. In some implementations, authentication may be with respect to an existing NFT. In other implementations, authentication may be with respect to an NFT that is being created. The disclosed implementations may compare a candidate and/or candidate NFT data with existing NFTs and/or existing NFT data to determine if the candidate NFT and/or candidate NFT data is similar to other NFTs and/or other NFT data of another NFT, which may exist on any of many different blockchains.Type: GrantFiled: August 4, 2021Date of Patent: May 14, 2024Assignee: Pinterest, Inc.Inventors: Evrhet Milam, Tiffany C. Black, Ryan Wilson Probasco, Will Fu, David Temple, Dmitry Olegovich Kislyuk, Andrey Dmitriyevich Gusev
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Publication number: 20240152754Abstract: Systems and methods for generating embeddings for nodes of a corpus graph are presented. More particularly, operations for generation of an aggregated embedding vector for a target node is efficiently divided among operations on a central processing unit and operations on a graphic processing unit. With regard to a target node within a corpus graph, processing by one or more central processing units (CPUs) is conducted to identify the target node's relevant neighborhood (of nodes) within the corpus graph. This information is prepared and passed to one or more graphic processing units (GPUs) that determines the aggregated embedding vector for the target node according to data of the relevant neighborhood of the target node.Type: ApplicationFiled: January 16, 2024Publication date: May 9, 2024Applicant: Pinterest, Inc.Inventors: Jurij Leskovec, Chantat Eksombatchai, Kaifeng Chen, Ruining He, Rex Ying
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Patent number: 11977554Abstract: A system for and a method of using user-entered information to return more meaningful information in response to Internet search queries are disclosed. A method in accordance with the disclosed subject matter comprises managing a database in response to multiple user inputs and displaying search results from the database in response to a search query. The search results include a results list and supplemental data related to the search query. Managing the database includes, among other things, re-ranking elements in the results list, storing information related to relevancies of elements in the results list, blocking a link in the results list, storing links to documents related to the search query, or any combination of these. The supplemental data include descriptions of or indices to one or more concepts related to the search query.Type: GrantFiled: May 16, 2023Date of Patent: May 7, 2024Assignee: Pinterest, Inc.Inventors: Michael Tanne, Yunshan Lu, Bruce D. Karsh
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Publication number: 20240135466Abstract: Systems and methods for generating user notifications to a set of users of a social networking service is presented. For each user of a set of users of the social networking service, one or more machine learning models selects an optimal notification channel, an optimal notification template, and optimal personalization content for configurable elements of a selected notification template. Each of these determinations/selections is made according to and based on a likelihood of increased user engagement with the social networking service. Upon determining the notification channel, notification template, and personalizations to the template, the notification is generated and sent to the corresponding user.Type: ApplicationFiled: January 3, 2024Publication date: April 25, 2024Applicant: Pinterest, Inc.Inventors: Bo Zhao, Samuel Seth Weisfeld-Filson, John William Gupta Egan, Burkay Birant Orten, Koichiro Narita
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Patent number: 11968409Abstract: Described are systems and methods for determining and/or generating a queue of content items to improve the playback experience of the content items for a user. The content items may be obtained, for example, by a client device from an online service in response to a query, a request for content items, and the like. Relevance rankings and/or scores associated with the content items may be replaced and/or augmented with a playability score, which can represent a quality of the playback experience associated with each content item. The playability score for each content item may be aggregated with the relevance and/or user engagement score associated with each content item to determine an overall playback score for each content item. The content items may be ranked, ordered, arranged, and/or presented in accordance with the overall playback scores associated with the content items to facilitate an improved playback experience for a user associated with the client device.Type: GrantFiled: April 26, 2022Date of Patent: April 23, 2024Assignee: Pinterest, Inc.Inventor: Liang Ma
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Patent number: 11960846Abstract: Systems and methods are presented for inferring an embedding vector of an item of a first type into the embedding space. Upon receiving a first time for which there is no embedding vector, documents of a document corpus that include (co-occurrence) both the received item and other items of the same type are identified. Of those other items that have embedding vectors, those embedding vectors are retrieved and averaged. The resulting averaged embedding vector is established as an inferred embedding vector for the received item.Type: GrantFiled: May 10, 2023Date of Patent: April 16, 2024Assignee: Pinterest, Inc.Inventors: Heath Vinicombe, Chenyi Li, Yunsong Guo, Yu Liu
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Patent number: 11947577Abstract: Systems and methods for providing auto-completion options to input characters are presented. In response to receiving input characters, a plurality of items of content (that are non-textual items of content) of a corpus of content are identified. These items of content are clustered into n clusters of content according to similarities among the items of content. From the items of content of each cluster, a descriptive title is determined for the cluster. This descriptive title is an auto-completion option for the cluster. The descriptive titles/auto-completion options are provided in response to receiving the input characters.Type: GrantFiled: June 24, 2021Date of Patent: April 2, 2024Assignee: Pinterest, Inc.Inventors: Jeffrey Harris, Lulu Cheng, Xixia Wang, Matthew Chun-Bong Fong, Joseph Vito Zingarelli, Long Cheng
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Patent number: 11935102Abstract: The described implementations enable a seller to sell items through multiple e-commerce channels without having to maintain independent merchant accounts at each channel. For example, a seller may sell items directly and through a management service. When a user request to purchase an item from the seller through the management service is received, the management service sends the purchase information to the seller so that the seller can complete the purchase as if the purchase were being made directly with the seller. Upon completion of the purchase, the seller provides a confirmation back to the management service and provides the item directly to the user.Type: GrantFiled: June 5, 2020Date of Patent: March 19, 2024Assignee: Pinterest, Inc.Inventors: Chao Wang, Michael Yamartino, Sridatta Kaustubh Thatipamala, Yuan Wei
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Patent number: 11928133Abstract: Described are systems and methods for establishing a unit group dictionary based on user provided annotations. The unit group dictionary may be used to identify relationships between multiple items in a corpus. Those relationships may facilitate the display of object identifiers and/or other aspects used and/or provided by the object management service.Type: GrantFiled: August 23, 2021Date of Patent: March 12, 2024Assignee: Pinterest, Inc.Inventors: Ningning Hu, Tze Way Eugene Ie
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Patent number: 11922308Abstract: Systems and methods for generating embeddings for nodes of a corpus graph are presented. More particularly, operations for generation of an aggregated embedding vector for a target node is efficiently divided among operations on a central processing unit and operations on a graphic processing unit. With regard to a target node within a corpus graph, processing by one or more central processing units (CPUs) is conducted to identify the target node's relevant neighborhood (of nodes) within the corpus graph. This information is prepared and passed to one or more graphic processing units (GPUs) that determines the aggregated embedding vector for the target node according to data of the relevant neighborhood of the target node.Type: GrantFiled: January 17, 2022Date of Patent: March 5, 2024Assignee: Pinterest, Inc.Inventors: Jurij Leskovec, Chantat Eksombatchai, Kaifeng Chen, Ruining He, Rex Ying
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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: 11907962Abstract: An online host for conducting a promotion campaign is presented. Online behaviors of subscribers exposed by the promotion campaign are tracked for determining conversion counts for the promotion campaign. For exposed subscribers whose online behaviors are not sufficiently available to the online host to determine conversion counts (non-measurable subscribers), a machine learning model is trained to predict conversion counts based on online behaviors that are conducted on internet locations under control of the online service, and further trained to determine an estimated error rate regarding the predicted conversion counts.Type: GrantFiled: May 19, 2022Date of Patent: February 20, 2024Assignee: Pinterest, Inc.Inventors: Sean R. McCurdy, Zheng Fang, Rohil Bhansali
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Patent number: 11900482Abstract: Systems and methods for generating user notifications to a set of users of a social networking service is presented. For each user of a set of users of the social networking service, one or more machine learning models selects an optimal notification channel, an optimal notification template, and optimal personalization content for configurable elements of a selected notification template. Each of these determinations/selections is made according to and based on a likelihood of increased user engagement with the social networking service. Upon determining the notification channel, notification template, and personalizations to the template, the notification is generated and sent to the corresponding user.Type: GrantFiled: June 14, 2021Date of Patent: February 13, 2024Assignee: Pinterest, Inc.Inventors: Bo Zhao, Samuel Seth Weisfeld-Filson, John William Gupta Egan, Burkay Birant Orten, Koichiro Narita