Sparse representations for text classification
US8566270B2 · kind B2 · utility
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15Claims
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Key dates
| Filing date | Sep 23, 2011 |
| Grant date | Oct 22, 2013 |
| Priority date | — |
| Expiry date | Jun 21, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F16/353
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A sparse representation method of text classification is described. An input text document is represented as a document feature vector y. A category dictionary H provides possible examples [h1; h2; . . . ; hn] of the document feature vector y. The input text document is classified using a sparse representation text classification algorithm that solves for y=Hβ where a sparseness condition is enforced on β to select a small number of examples from the dictionary H to describe the document feature vector y.
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