System and method of feature selection for text classification using subspace sampling
US8046317B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 31, 2007 |
| Grant date | Oct 25, 2011 |
| Priority date | — |
| Expiry date | Aug 26, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F18/2411
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An improved system and method is provided for feature selection for text classification using subspace sampling. A text classifier generator may be provided for selecting a small set of features using subspace sampling from the corpus of training data to train a text classifier for using the small set of features for classification of texts. To select the small set of features, a subspace of features from the corpus of training data may be randomly sampled according to a probability distribution over the set of features where a probability may be assigned to each of the features that is proportional to the square of the Euclidean norms of the rows of left singular vectors of a matrix of the features representing the corpus of training texts. The small set of features may classify texts using only the relevant features among a very large number of training features.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.