Invention Grant
- Patent Title: Key-value memory network for predicting time-series metrics of target entities
-
Application No.: US17960585Application Date: 2022-10-05
-
Publication No.: US11694165B2Publication Date: 2023-07-04
- Inventor: Ayush Chauhan , Shiv Kumar Saini , Parth Gupta , Archiki Prasad , Amireddy Prashanth Reddy , Ritwick Chaudhry
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: Kilpatrick Townsend & Stockton LLP
- The original application number of the division: US16868942 2020.05.07
- Main IPC: G06F18/214
- IPC: G06F18/214 ; G06N3/063 ; G06F18/24 ; G11C16/14 ; G06Q10/109 ; G06F7/544

Abstract:
A system implements a key value memory network including a key matrix with key vectors learned from training static feature data and time-series feature data, a value matrix with value vectors representing time-series trends, and an input layer to receive, for a target entity, input data comprising a concatenation of static feature data of the target entity, time-specific feature data, and time-series feature data for the target entity. The key value memory network also includes an entity-embedding layer to generate an input vector from the input data, a key-addressing layer to generate a weight vector indicating similarities between the key vectors and the input vector, a value-reading layer to compute a context vector from the weight and value vectors, and an output layer to generate predicted time-series data for a target metric of the target entity by applying a continuous activation function to the context vector and the input vector.
Public/Granted literature
- US20230031050A1 KEY-VALUE MEMORY NETWORK FOR PREDICTING TIME-SERIES METRICS OF TARGET ENTITIES Public/Granted day:2023-02-02
Information query