Invention Grant
- Patent Title: Embedding multi-modal time series and text data
-
Application No.: US17370498Application Date: 2021-07-08
-
Publication No.: US11741146B2Publication Date: 2023-08-29
- Inventor: Yuncong Chen , Dongjin Song , Cristian Lumezanu , Haifeng Chen , Takehiko Mizoguchi , Xuchao Zhang
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: US NJ Princeton
- Assignee: NEC Laboratories America, Inc.
- Current Assignee: NEC Laboratories America, Inc.
- Current Assignee Address: US NJ Princeton
- Agent Joseph Kolodka
- Main IPC: G06F16/35
- IPC: G06F16/35 ; G06K9/62 ; G06F40/169 ; G06N3/08 ; G06F18/23 ; G06F18/214 ; G06V10/77 ; G06V10/82 ; G06V10/62

Abstract:
Methods and systems of training and using a neural network model include training a time series embedding model and a text embedding model with unsupervised clustering to translate time series and text, respectively, to a shared latent space. The time series embedding model and the text embedding model are further trained using semi-supervised clustering that samples training data pairs of time series information and associated text for annotation.
Public/Granted literature
- US20220012274A1 EMBEDDING MULTI-MODAL TIME SERIES AND TEXT DATA Public/Granted day:2022-01-13
Information query