Method and system of iteratively autotuning prediction parameters in a media content recommender
US9495645B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 30, 2013 |
| Grant date | Nov 15, 2016 |
| Priority date | — |
| Expiry date | Aug 1, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/637
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one exemplary embodiment, a method of a computerized media-content recommender includes receiving a user-judgment score based on an historical user-listening data with respect to a media content. A first prediction score for a user with respect to the media content is calculated with a media-content recommender. The media-content recommender includes a first set of prediction parameters. A first prediction error including a difference between the user-judgment score and the first prediction score is determined. At least one parameter value of the first set of prediction parameters is modified with a machine-learning optimization technique to generate a second set of prediction parameters. A second prediction score for the user with respect to the media content is calculated with a media-content recommender. A second prediction error including a difference between the user-judgment score and the second prediction score is calculated.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.