Invention Grant
- Patent Title: Aggregate features for machine learning
-
Application No.: US15675671Application Date: 2017-08-11
-
Publication No.: US10649794B2Publication Date: 2020-05-12
- Inventor: Sean Moon , Arvind Thiagarajan , Mike Jahr , Milind Ganjoo , Parag Agrawal
- Applicant: Twitter, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Twitter, Inc.
- Current Assignee: Twitter, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Brake Hughes Bellermann LLP
- Main IPC: G06F16/00
- IPC: G06F16/00 ; G06F9/445 ; G06F16/903 ; H04L29/06 ; G06F21/55 ; G06F16/9032 ; G06N20/00 ; G06N3/08 ; G06Q50/00

Abstract:
An example system includes a memory store of aggregate definitions. Each aggregate definition specifies a key value, an output store, a feature, a half-life value, and an aggregate operation metric to apply to a cross of the feature and the half-life value to generate aggregate metrics. The system also includes an aggregation engine that generates aggregate feature records from the input source based on the aggregate definitions and stores the aggregate feature records in the output store. An aggregate feature record includes an aggregate of the metric for the feature decayed over time using the half-life. The system also includes a query service that identifies, using the aggregate definitions, responsive aggregate feature records that satisfy parameters of a received request, applies the half-life to the responsive feature records, and provides the responsive feature records to a requester, the requester using the responsive feature records as input for a neural network.
Public/Granted literature
- US20180046918A1 Aggregate Features For Machine Learning Public/Granted day:2018-02-15
Information query