Learning ranking functions incorporating boosted ranking in a regression framework for information retrieval and ranking
US8051072B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 31, 2008 |
| Grant date | Nov 1, 2011 |
| Priority date | — |
| Expiry date | Sep 13, 2029 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/951
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments of the present invention provide for methods, systems and computer program products for learning ranking functions to determine the ranking of one or more content items that are responsive to a query. The present invention includes generating one or more training sets comprising one or more content item-query pairs, determining preference data for the one or more query-content item pairs of the one or more training sets and determining labeled data for the one or more query-content item pairs of the one or more training sets. A ranking function is determined based upon the preference data and the labeled data for the one or more content-item query pairs of the one or more training sets. The ranking function is then stored for application to query-content item pairs not contained in the one or more training sets.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.