Invention Grant
- Patent Title: Predictive recommendation system using absolute relevance
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Application No.: US17125158Application Date: 2020-12-17
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Publication No.: US11587123B2Publication Date: 2023-02-21
- Inventor: Lawrence Lee Wai
- Applicant: Groupon, Inc.
- Applicant Address: US IL Chicago
- Assignee: Groupon, Inc.
- Current Assignee: Groupon, Inc.
- Current Assignee Address: US IL Chicago
- Agency: Alston & Bird LLP
- Main IPC: G06Q30/02
- IPC: G06Q30/02 ; G06Q30/0251 ; G06Q30/0242 ; G06Q30/0207 ; G06Q30/0241

Abstract:
In general, embodiments of the present invention provide systems, methods and computer readable media for ranking promotions selected for recommendation to consumers based on predictions of promotion performance and consumer behavior. In embodiments, a set of promotions to be recommended to a consumer can be sorted and/or ranked according to respective relevance scores representing a probability that the consumer's behavior in response to the promotion will match a ranking target. In embodiments, calculating scores is based on a relevance model (a predictive function) derived from one or more contextual data sources representing attributes of promotions and consumer behavior. In embodiments, an absolute relevance score represents an absolute prediction of a ranking target variable. In embodiments, absolute relevance may be used to determine personalized local merchant discovery frontiers; featured result set thresholding for impressions; and/or promotion notification triggers. In embodiments, predictive models based on gross revenue may be optimized using promotion category-dependent price boosting.
Public/Granted literature
- US20210174399A1 Predictive Recommendation System Using Absolute Relevance Public/Granted day:2021-06-10
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