公开(公告)号：US20250148192A1

公开(公告)日：2025-05-08

申请号：US18501745

申请日：2023-11-03

Applicant: Adobe Inc.

Inventor： Simra SHAHID ,  Nikitha SRIKANTH ,  Surgan JANDAIL ,  Balaji KRISHNAMURTHY

IPC: G06F40/166 ,  G06F16/9538 ,  G06F40/194

Abstract: Methods, computer systems, computer-storage media, and graphical user interfaces are provided for efficiently generating alternative examples for content. In embodiments, a source example prompt is obtained at a large language model. The source example prompt includes text associated with a source content and an instruction to generate a source example from the text associated with the source content. Using the large language model, the source example that represents an entity and corresponding context from the text is generated. Thereafter, the source example and a set of user segments are provided as input into the large language model to generate alternative examples associated with the source content. Each alternative example corresponds to a user segment of the set of user segments. Based on a particular user segment associated with a user interested in the source content, an alternative example corresponding to the particular user segment is provided for display.

公开(公告)号：US20230143777A1

公开(公告)日：2023-05-11

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

CPC classification number: 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.