Using IR techniques to improve Automated Text Classification
| dc.contributor.author | Gonçalves, Teresa | |
| dc.contributor.author | Quaresma, Paulo | |
| dc.date.accessioned | 2011-02-15T10:54:06Z | |
| dc.date.available | 2011-02-15T10:54:06Z | |
| dc.date.issued | 2004 | |
| dc.description.abstract | This paper performs a study on the pre-processing phase of the automated text classification problem. We use the linear Support Vector Machine paradigm applied to datasets written in the English and the European Portuguese languages – the Reuters and the Portuguese Attorney General’s Office datasets, respectively. The study can be seen as a search, for the best document representa- tion, in three different axes: the feature reduction (using linguistic in- formation), the feature selection (using word frequencies) and the term weighting (using information retrieval measures). | en |
| dc.format.extent | 129335 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.accesstype | livre | en |
| dc.identifier.authoremail | tcg@uevora.pt | |
| dc.identifier.authoremail | pq@uevora.pt | |
| dc.identifier.editorperson | Meziane, F. | |
| dc.identifier.editorperson | Metais, E. | |
| dc.identifier.numrev | 3136 | en |
| dc.identifier.pagina | 374-379 | en |
| dc.identifier.principalpublicationtitle | NLDB-04, Natural Language Processing and Information Systems | en |
| dc.identifier.revista | Lecture Notes in Computer Science | en |
| dc.identifier.scientificarea | 498 | en |
| dc.identifier.uri | http://hdl.handle.net/10174/2557 | |
| dc.language.iso | eng | |
| dc.peerreviewed | no | en |
| dc.publisher | Springer-Verlag | en |
| dc.rights | openAccess | en |
| dc.subject | machine learning | en |
| dc.subject | Text classification | en |
| dc.title | Using IR techniques to improve Automated Text Classification | en |
| dc.type | article | en |