公开(公告)号：US12008033B2

公开(公告)日：2024-06-11

申请号：US17447908

申请日：2021-09-16

Applicant: ADOBE INC.

Inventor： Yaman Kumar ,  Vinh Ngoc Khuc ,  Vijay Srivastava ,  Umang Moorarka ,  Sukriti Verma ,  Simra Shahid ,  Shirsh Bansal ,  Shankar Venkitachalam ,  Sean Steimer ,  Sandipan Karmakar ,  Nimish Srivastav ,  Nikaash Puri ,  Mihir Naware ,  Kunal Kumar Jain ,  Kumar Mrityunjay Singh ,  Hyman Chung ,  Horea Bacila ,  Florin Silviu Iordache ,  Deepak Pai ,  Balaji Krishnamurthy

IPC: G06F7/02 ,  G06F16/00 ,  G06F16/535 ,  G06F16/54 ,  G06F16/58 ,  G06F16/583 ,  G06N20/00

CPC classification number: G06F16/5866 ,  G06F16/535 ,  G06F16/54 ,  G06F16/583 ,  G06N20/00

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for determining user affinities by tracking historical user interactions with tagged digital content and using the user affinities in content generation applications. Accordingly, the system may track user interactions with published digital content in order to generate user interaction reports whenever a user engages with the digital content. The system may aggregate the interaction reports to generate an affinity profile for a user or audience of users. A marketer may then generate digital content for a target user or audience of users and the system may process the digital content to generate a set of tags for the digital content. Based on the set of tags, the system may then evaluate the digital content in view of the affinity profile for the target user/audience to determine similarities or differences between the digital content and the affinity profile.

公开(公告)号：US11960520B2

公开(公告)日：2024-04-16

申请号：US17853141

申请日：2022-06-29

Applicant: Adobe Inc.

Inventor： Tanay Anand ,  Sumit Bhatia ,  Simra Shahid ,  Nikitha Srikanth ,  Nikaash Puri

IPC: G06F16/30 ,  G06F16/33 ,  G06F16/35 ,  G06F16/93 ,  G06F18/2133 ,  G06F18/2413 ,  G06F40/30

CPC classification number: G06F16/35 ,  G06F16/3347 ,  G06F16/93 ,  G06F18/2133 ,  G06F18/24147 ,  G06F40/30

Abstract: Some techniques described herein relate to generating a hierarchical topic model (HTM), which can be used to generate custom content. In one example, a method includes determining first-level topics in a topic hierarchy related to a corpus of documents. A first-level topic of the first-level topics includes multiple words. The multiple words are grouped into clusters based on word embeddings of the multiple words. The multiple words are then subdivided into second-level topics as subtopics of the first-level topic, such that the number of second-level topics equals the number of clusters. A document of the corpus of documents is assigned to the first-level topic and to a second-level topic of the second-level topics, and an indication is received of access by a user to the document. Custom content is generated for the user based on one or more other documents assigned to the first-level topic and the second-level topic.

公开(公告)号：US12190061B2

公开(公告)日：2025-01-07

申请号：US17644856

申请日：2021-12-17

Applicant: ADOBE INC.

Inventor： Shashank Shailabh ,  Madhur Panwar ,  Milan Aggarwal ,  Pinkesh Badjatiya ,  Simra Shahid ,  Nikaash Puri ,  S Sejal Naidu ,  Sharat Chandra Racha ,  Balaji Krishnamurthy ,  Ganesh Karbhari Palwe

IPC: G06F40/289 ,  G06F40/30 ,  G06F40/40

Abstract: Systems and methods for topic modeling are described. The systems and methods include encoding words of a document using an embedding matrix to obtain word embeddings for the document. The words of the document comprise a subset of words in a vocabulary, and the embedding matrix is trained as part of a topic attention network based on a plurality of topics. The systems and methods further include encoding a topic-word distribution matrix using the embedding matrix to obtain a topic embedding matrix. The topic-word distribution matrix represents relationships between the plurality of topics and the words of the vocabulary. The systems and methods further include computing a topic context matrix based on the topic embedding matrix and the word embeddings and identifying a topic for the document based on the topic context matrix.

公开(公告)号：US20250103822A1

公开(公告)日：2025-03-27

申请号：US18372462

申请日：2023-09-25

Applicant: Adobe Inc.

Inventor： Niranjan Kumbi ,  Sreekanth Reddy ,  Sumit Bhatia ,  Milan Aggarwal ,  Simra Shahid ,  Nikitha Srikanth ,  Camille Girabawe ,  Narayanan Seshadri

IPC: G06F40/35

Abstract: System and methods for generating, validating, and augmenting question-answer pairs using generative AI are provided. An online interaction server accesses a set of digital content available at a set of designated network locations. The online interaction server further trains a pre-trained large language model (LLM) using the set of digital content to obtain a customized LLM. The online interaction server generates a set of question-answer pairs based on the set of digital content using the customized LLM and validates the set of question-answer pairs by determining if an answer in a question-answer pair is derived from the set of digital content. The online interaction server also selects a digital asset to augment an answer in a validated question-answer pair based on a semantic similarity between the validated question-answer pair and the digital asset.

公开(公告)号：US20240289380A1

公开(公告)日：2024-08-29

申请号：US18656332

申请日：2024-05-06

Applicant: Adobe Inc.

Inventor： Yaman Kumar ,  Vinh Ngoc Khuc ,  Vijay Srivastava ,  Umang Moorarka ,  Sukriti Verma ,  Simra Shahid ,  Shirsh Bansal ,  Shankar Venkitachalam ,  Sean Steimer ,  Sandipan Karmakar ,  Nimish Srivastav ,  Nikaash Puri ,  Mihir Naware ,  Kunal Kumar Jain ,  Kumar Mrityunjay Singh ,  Hyman Chung ,  Horea Bacila ,  Florin Silviu Lordache ,  Deepak Pai ,  Balaji Krishnamurthy

IPC: G06F16/58 ,  G06F16/535 ,  G06F16/54 ,  G06F16/583 ,  G06N20/00

CPC classification number: G06F16/5866 ,  G06F16/535 ,  G06F16/54 ,  G06F16/583 ,  G06N20/00

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for determining user affinities by tracking historical user interactions with tagged digital content and using the user affinities in content generation applications. Accordingly, the system may track user interactions with published digital content in order to generate user interaction reports whenever a user engages with the digital content. The system may aggregate the interaction reports to generate an affinity profile for a user or audience of users. A marketer may then generate digital content for a target user or audience of users and the system may process the digital content to generate a set of tags for the digital content. Based on the set of tags, the system may then evaluate the digital content in view of the affinity profile for the target user/audience to determine similarities or differences between the digital content and the affinity profile.

公开(公告)号：US20230085466A1

公开(公告)日：2023-03-16

申请号：US17447908

申请日：2021-09-16

Applicant: ADOBE INC.

Inventor： Yaman Kumar ,  Vinh Ngoc Khuc ,  Vijay Srivastava ,  Umang Moorarka ,  Sukriti Verma ,  Simra Shahid ,  Shirsh Bansal ,  Shankar Venkitachalam ,  Sean Steimer ,  Sandipan Karmakar ,  Nimish Srivastav ,  Nikaash Puri ,  Mihir Naware ,  Kunal Kumar Jain ,  Kumar Mrityunjay Singh ,  Hyman Chung ,  Horea Bacila ,  Florin Silviu Iordache ,  Deepak Pai ,  Balaji Krishnamurthy

IPC: G06F16/58 ,  G06N20/00 ,  G06F16/535 ,  G06F16/583 ,  G06F16/54

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for determining user affinities by tracking historical user interactions with tagged digital content and using the user affinities in content generation applications. Accordingly, the system may track user interactions with published digital content in order to generate user interaction reports whenever a user engages with the digital content. The system may aggregate the interaction reports to generate an affinity profile for a user or audience of users. A marketer may then generate digital content for a target user or audience of users and the system may process the digital content to generate a set of tags for the digital content. Based on the set of tags, the system may then evaluate the digital content in view of the affinity profile for the target user/audience to determine similarities or differences between the digital content and the affinity profile.

公开(公告)号：US12223002B2

公开(公告)日：2025-02-11

申请号：US17454445

申请日：2021-11-10

Applicant: ADOBE INC.

Inventor： Pinkesh Badjatiya ,  Tanay Anand ,  Simra Shahid ,  Nikaash Puri ,  Milan Aggarwal ,  S Sejal Naidu ,  Sharat Chandra Racha

IPC: G06F16/9536 ,  G06F16/9538 ,  G06F40/20

Abstract: A method of finding online relevant conversing posts, comprises receiving, by a web server serving an online forum, a query post from an inquirer using the online forum, computing a contextual similarity score between each conversing post of a set of conversing posts with a query post, wherein the contextual similarity score is computed between the body of each of conversing posts and of the query post, wherein N1 conversing posts with a highest contextual similarity score are selected; computing a fine grained similarity score between the subject of the query post and of each of the N1 conversing posts, wherein N2 conversing posts with a highest fine grained similarity score are selected; and boosting the fine grained similarity score of the N2 conversing posts based on relevance metrics, wherein N3 highest ranked conversing posts are selected as a list of conversing posts most relevant to the query post.

公开(公告)号：US20240004912A1

公开(公告)日：2024-01-04

申请号：US17853141

申请日：2022-06-29

Applicant: Adobe Inc.

Inventor： Tanay Anand ,  Sumit Bhatia ,  Simra Shahid ,  Nikitha Srikanth ,  Nikaash Puri

IPC: G06F16/35 ,  G06K9/62 ,  G06F16/93 ,  G06F40/30 ,  G06F16/33

CPC classification number: G06F16/35 ,  G06K9/6239 ,  G06K9/6276 ,  G06F16/93 ,  G06F40/30 ,  G06F16/3347

Abstract: Some techniques described herein relate to generating a hierarchical topic model (HTM), which can be used to generate custom content. In one example, a method includes determining first-level topics in a topic hierarchy related to a corpus of documents. A first-level topic of the first-level topics includes multiple words. The multiple words are grouped into clusters based on word embeddings of the multiple words. The multiple words are then subdivided into second-level topics as subtopics of the first-level topic, such that the number of second-level topics equals the number of clusters. A document of the corpus of documents is assigned to the first-level topic and to a second-level topic of the second-level topics, and an indication is received of access by a user to the document. Custom content is generated for the user based on one or more other documents assigned to the first-level topic and the second-level topic.

公开(公告)号：US20230169271A1

公开(公告)日：2023-06-01

申请号：US17644856

申请日：2021-12-17

Applicant: ADOBE INC.

Inventor： Shashank Shailabh ,  Madhur Panwar ,  Milan Aggarwal ,  Pinkesh Badjatiya ,  Simra Shahid ,  Nikaash Puri ,  S Sejal Naidu ,  Sharat Chandra Racha ,  Balaji Krishnamurthy ,  Ganesh Karbhari Palwe

IPC: G06F40/289 ,  G06F40/40 ,  G06F40/30

CPC classification number: G06F40/289 ,  G06F40/40 ,  G06F40/30

Abstract: Systems and methods for topic modeling are described. The systems and methods include encoding words of a document using an embedding matrix to obtain word embeddings for the document. The words of the document comprise a subset of words in a vocabulary, and the embedding matrix is trained as part of a topic attention network based on a plurality of topics. The systems and methods further include encoding a topic-word distribution matrix using the embedding matrix to obtain a topic embedding matrix. The topic-word distribution matrix represents relationships between the plurality of topics and the words of the vocabulary. The systems and methods further include computing a topic context matrix based on the topic embedding matrix and the word embeddings and identifying a topic for the document based on the topic context matrix.