Enhancing robustness of pseudo-relevance feedback models using query drift minimization
US11222277B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 29, 2016 |
| Grant date | Jan 11, 2022 |
| Priority date | — |
| Expiry date | Sep 4, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A pseudo-relevance feedback (PRF) system is disclosed that determines an optimized relevance model for a search query by utilizing a posterior relevance model to estimate the likelihood that an initial set of top-K retrieved documents would be retrieved given the posterior relevance model, re-ranking the top-K documents based on their respective estimates of likelihood of retrieval, determining a rank similarity between the initial ranking of the top-K documents and the re-ranking of the top-K documents, updating one or more model parameters of the posterior relevance model based on the rank similarity, and iteratively performing the above process until the rank similarity is maximized, at which point, the optimized relevance model is obtained.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.