Dynamic filter recommendations
US11727014B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 12, 2019 |
| Grant date | Aug 15, 2023 |
| Priority date | — |
| Expiry date | Mar 18, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A user preference hierarchy is determined from user response to images. Images may be tagged using machine learning models trained to determine values for images. Products are clustered according to product vectors. Images of products within a cluster are clustered according to composition and groups of images are selected from image clusters for soliciting feedback regarding user preference for products of a cluster. Feedback is used to train a user preference model to estimate affinity for a product vector. A user may provide feedback regarding a price point and products are weighted according to a distribution about the price point. The distribution may be asymmetrical according to direction of movement of the price point. Filters may be dynamically defined and presented to a user based on popularity and frequency of occurrence of attribute-value pairs of search results and based on feedback regarding the search results.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.