Invention Grant
- Patent Title: Tunable algorithmic segments
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Application No.: US13726308Application Date: 2012-12-24
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Publication No.: US10373197B2Publication Date: 2019-08-06
- Inventor: Nicholas M. Jordon , Margarita R. Savova , Matvey Kapilevich , Paul Mackles , David M. Weinstein
- Applicant: Adobe Inc.
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.
- Current Assignee: Adobe Inc.
- Current Assignee Address: US CA San Jose
- Agency: SBMC
- Main IPC: G06Q30/02
- IPC: G06Q30/02

Abstract:
Tunable algorithmic segment techniques are described. In one or more implementations, a target audience definition is obtained that is input to initiate creation of a look-alike model. The target audience definition indicates traits associated with a baseline group of consumers who have interacted with online resources in a designated manner, such as by buying a product, visiting a website, using a service, and so forth. Tuning parameters designated for the look-alike model are ascertained and the look-alike model is built based on the target audience definition and the tuning parameters. The tuning parameters may include at least a setting selectable to control reach versus accuracy for the look-alike model. Segment data indicative of market segments generated according to the look-alike model may then be exposed for manipulation by a client. The manipulation may include selectable control over the tuning parameters to generate different look-alike groups from the segment data.
Public/Granted literature
- US20140180804A1 Tunable Algorithmic Segments Public/Granted day:2014-06-26
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