Invention Grant
- Patent Title: Feature generation for online/offline machine learning
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Application No.: US15331106Application Date: 2016-10-21
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Publication No.: US10432689B2Publication Date: 2019-10-01
- Inventor: Mohammad Hossein Taghavi , Prasanna Padmanabhan , Dong-Bang Tsai , Faisal Zakaria Siddiqi , Justin Derrick Basilico
- Applicant: NETFLIX, Inc
- Applicant Address: US CA Los Gatos
- Assignee: Netflix, Inc.
- Current Assignee: Netflix, Inc.
- Current Assignee Address: US CA Los Gatos
- Agency: FisherBroyles, LLP
- Main IPC: H04L29/06
- IPC: H04L29/06 ; H04L29/08 ; G06N5/04 ; G06N20/00 ; H04N21/24 ; G06F16/335 ; G06F16/9535 ; H04N21/25 ; H04N21/258

Abstract:
A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.
Public/Granted literature
- US20170237792A1 Feature Generation for Online/Offline Machine Learning Public/Granted day:2017-08-17
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