Enhanced max margin learning on multimodal data mining in a multimedia database
US10007679B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 29, 2014 |
| Grant date | Jun 26, 2018 |
| Priority date | — |
| Expiry date | May 9, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/764
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Multimodal data mining in a multimedia database is addressed as a structured prediction problem, wherein mapping from input to the structured and interdependent output variables is learned. A system and method for multimodal data mining is provided, comprising defining a multimodal data set comprising image information; representing image information of a data object as a set of feature vectors in a feature space; clustering in the feature space to group similar features; associating a non-image representation with a respective image data object based on the clustering; determining a joint feature representation of a respective data object as a mathematical weighted combination of a set of components of the joint feature representation; optimizing a weighting for a plurality of components of the mathematical weighted combination with respect to a prediction error between a predicted classification and a training classification; and employing the mathematical weighted combination for automatically classifying a new data object.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.