LINEAR-PROGRAMMING-BASED RECOMMENDER WITH PERSONALIZED DIVERSITY CONSTRAINTS
Number of patents in Portfolio can not be more than 2000
United States of America Patent
Stats
-
N/A
Issued Date -
Jun 20, 2024
app pub date -
Dec 7, 2022
filing date -
Dec 7, 2022
priority date (Note) -
Published
status (Latency Note)
Importance
Abstract
In an example embodiment, a structured linear program is provided that is usable in recommender models. This structured linear program is able to produce real-time results for a structured recommendation problem with diversity constraints, even for large data sets. The structured linear program operates by first reducing a two-sided diversity constraint to a one-sided diversity constraint, and then introducing a dual variable for a constraint, in order to define a dual objective function. The dual objective function is then solved using a bisection method. A primal solution is then recovered using the solved dual objective function. The resultant primal solution reflects a set of recommended content items that satisfy the diversity constraint, as computed in real-time.
First Claim
Family
International Classification(s)
- [Classification Symbol]
- [Patents Count]
Cited Art Landscape
Patent Citation Ranking
Recipient Email Address
Recipient Email Address
Comment
Recipient Email Address
Add to Portfolio(s)
To add this patent to one, or more, of your portfolios, simply click the add button.
This Patent is in these Portfolios:
Add to additional portfolios:
Last Refreshed On:
Changes done successfully