Method and appartus for using B measures to learn balanced relevance functions from expert and user judgments
US7685078B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 30, 2007 |
| Grant date | Mar 23, 2010 |
| Priority date | — |
| Expiry date | Oct 29, 2028 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/951
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present invention relates to systems and methods for determining a content item relevance function. The method comprises collecting user preference data at a search provider for storage in a user preference data store and collecting expert-judgment data at the search provider for storage in an expert sample data store. A modeling module trains a base model through the use of the expert-judgment data and tunes the base model through the use of the user preference data to learn a set of one or more tuned models. A measure (B measure) is designed to evaluate the balanced performance of tuned model over expert judgment and user preference. The modeling module generates or selects the content item relevance function from the tuned models with B measure as the selection criterion.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.