Invention Grant
- Patent Title: Machine learning-based media content sequencing and placement
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Application No.: US16022161Application Date: 2018-06-28
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Publication No.: US11270337B2Publication Date: 2022-03-08
- Inventor: Glenn J. Kiladis , Aron Robert Schatz
- Applicant: ViralGains Inc.
- Applicant Address: US MA Boston
- Assignee: ViralGains Inc.
- Current Assignee: ViralGains Inc.
- Current Assignee Address: US MA Boston
- Agency: Patent GC LLC
- Agent Alexander Franco
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06Q30/02 ; G06N3/08 ; G06N7/00 ; H04L67/50 ; G06F16/735

Abstract:
A system performs an automated analysis on a set of related media content items, such as static and video display advertisements for a coordinated advertising campaign. The analysis can include, for example, recognition of products, services, brands, objects, music, speech, motion, colors and moods, in order to determine content profiles for the content items. Different sequences of the media content items are placed within the web browsing paths of individual users, and the responses to the sequences are monitored with respect to desired outcomes, such as the purchase of a product or the visiting of an advertiser's website. The content profiles, the sequences, the placements, and the responses are provided as input into a machine learning system that is trained to select sequences and placements of media content items that achieve the desired outcomes. The system can be trained in part or wholly using feedback from its own output.
Public/Granted literature
- US20190139086A1 Machine Learning-Based Media Content Sequencing and Placement Public/Granted day:2019-05-09
Information query