Online diverse set generation from partial-click feedback
US10984058B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 8, 2018 |
| Grant date | Apr 20, 2021 |
| Priority date | — |
| Expiry date | Jul 30, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/02
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A machine-learning framework uses partial-click feedback to generate an optimal diverse set of items. An example method includes estimating a preference vector for a user based on diverse cascade statistics for the user, the diverse cascade statistics including previously observed responses and previously observed topic gains. The method also includes generating an ordered set of items from the item repository, the items in the ordered set having highest topic gain weighted by similarity with the preference vector, providing the ordered set for presentation to the user, and receiving feedback from the user on the ordered set. The method also includes, responsive to the feedback indicating a selected item, updating the diverse cascade statistics for observed items, wherein the updating results in penalizing the topic gain for items of the observed items that are not the selected item and promoting the topic gain for the selected item.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.