公开(公告)号：US12242491B2

公开(公告)日：2025-03-04

申请号：US17716653

申请日：2022-04-08

Applicant: Microsoft Technology Licensing, LLC

Inventor： Ji Li ,  Dachuan Zhang ,  Amit Srivastava ,  Adit Krishnan

IPC: G06F16/2457 ,  G06F16/22 ,  G06F18/214 ,  G06N20/00

Abstract: A system and method and for retrieving assets from a personalized asset library includes receiving a search query for searching for assets in one or more asset libraries, the one or more asset libraries including a personalized asset library; encoding the search query into embedding representations via a trained query representation machine-learning (ML) model; comparing, via a matching unit, the query embedding representations to a plurality of asset representations, each of the plurality of asset representations being a representation of one of the plurality of candidate assets; identifying, based on the comparison, at least one of the plurality of the candidate assets as a search result for the search query; and providing the identified plurality of candidate assets for display as the search result. The plurality of asset representations for the one or more assets in the personalized content library are generated automatically without human labeling.

公开(公告)号：US12045279B2

公开(公告)日：2024-07-23

申请号：US17538880

申请日：2021-11-30

Applicant: Microsoft Technology Licensing, LLC

Inventor： Ji Li ,  Adit Krishnan ,  Amit Srivastava ,  Han Hu ,  Qi Dai ,  Yixuan Wei ,  Yue Cao

IPC: G06F16/58 ,  G06F16/51 ,  G06F16/56 ,  G06N20/00

CPC classification number: G06F16/5866 ,  G06F16/51 ,  G06F16/56 ,  G06N20/00

Abstract: A system and method and for retrieving one or more visual assets includes receiving a search query for the one or more visual assets, the search query including textual data, encoding the textual data into one or more text embedding representations via a trained text representation machine-learning (ML) model, transmitting the one or more text embedding representations to a matching and selection unit, providing visual embedding representations of one or more visual assets to the matching and selection unit, comparing, by the matching and selection unit, the one or more text embedding representations to the visual embedding representations to identify one or more visual asset search results, and providing the one or more visual asset search results for display.

公开(公告)号：US11841911B2

公开(公告)日：2023-12-12

申请号：US17530982

申请日：2021-11-19

Applicant: Microsoft Technology Licensing, LLC

Inventor： Ji Li ,  Amit Srivastava ,  Adit Krishnan ,  Aman Malik

IPC: G06F17/00 ,  G06F16/953 ,  G06N20/00

CPC classification number: G06F16/953 ,  G06N20/00

Abstract: A data processing system implements receiving query text for a search query for textual content recommendation. The query text includes one or more words indicating a type of textual content items being sought. The system implements analyzing the query text using a first machine learning (ML) model to obtain encoded query text, where the first ML model is trained to identify features within the query text and to generate the encoded query text by mapping the features to a hyper-dimensional latent space (HDLS). The system implements identifying one or more content items in a database of encoded content items mapped to the HDLS that satisfy the search query by comparing attributes of the encoded query text with attributes of the encoded content items to identify content items that are closest to the encoded query text within the HDLS, and causing the one or more content items to be displayed.