Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.creator | Soto, Axel Juan | - |
| dc.creator | Strickert, Marc | - |
| dc.creator | Vazquez, Gustavo Esteban | - |
| dc.creator | Milios, Evangelos | - |
| dc.date | 2018-12-21T18:27:38Z | - |
| dc.date | 2018-12-21T18:27:38Z | - |
| dc.date | 2011-05 | - |
| dc.date | 2018-12-21T15:21:51Z | - |
| dc.date.accessioned | 2019-04-29T15:30:58Z | - |
| dc.date.available | 2019-04-29T15:30:58Z | - |
| dc.date.issued | 2011-05 | - |
| dc.identifier | Soto, Axel Juan; Strickert, Marc; Vazquez, Gustavo Esteban; Milios, Evangelos; Subspace Mapping of Noisy Text Documents; Springer Verlag Berlín; Lecture Notes in Computer Science; 6657; 5-2011; 377-383 | - |
| dc.identifier | 0302-9743 | - |
| dc.identifier | http://hdl.handle.net/11336/66925 | - |
| dc.identifier | CONICET Digital | - |
| dc.identifier | CONICET | - |
| dc.identifier.uri | http://rodna.bn.gov.ar:8080/jspui/handle/bnmm/295546 | - |
| dc.description | Subspace mapping methods aim at projecting high-dimensional data into a subspace where a specific objective function is optimized. Such dimension reduction allows the removal of collinear and irrelevant variables for creating informative visualizations and task-related data spaces. These specific and generally de-noised subspaces spaces enable machine learning methods to work more eficiently. We present a new and general subspace mapping method, Correlative Matrix Mapping (CMM), and evaluate its abilities for category-driven text organization by assessing neighborhood preservation, class coherence, and classification. This approach is evaluated for the challenging task of processing short and noisy documents. | - |
| dc.description | Fil: Soto, Axel Juan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Dalhousie University Halifax; Canadá | - |
| dc.description | Fil: Strickert, Marc. Siegen University; Alemania | - |
| dc.description | Fil: Vazquez, Gustavo Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación; Argentina | - |
| dc.description | Fil: Milios, Evangelos. Dalhousie University Halifax; Canadá | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.publisher | Springer Verlag Berlín | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/chapter/10.1007/978-3-642-21043-3_45?LI=true | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/doi/https://doi.org/10.1007/978-3-642-21043-3_45 | - |
| dc.rights | info:eu-repo/semantics/restrictedAccess | - |
| dc.rights | https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ | - |
| dc.source | reponame:CONICET Digital (CONICET) | - |
| dc.source | instname:Consejo Nacional de Investigaciones Científicas y Técnicas | - |
| dc.source | instacron:CONICET | - |
| dc.subject | Mapping Method | - |
| dc.subject | Properties Prediction | - |
| dc.subject | Ciencias de la Computación | - |
| dc.subject | Ciencias de la Computación e Información | - |
| dc.subject | CIENCIAS NATURALES Y EXACTAS | - |
| dc.title | Subspace Mapping of Noisy Text Documents | - |
| dc.type | info:eu-repo/semantics/article | - |
| dc.type | info:eu-repo/semantics/publishedVersion | - |
| dc.type | info:ar-repo/semantics/articulo | - |
| Aparece en las colecciones: | CONICET | |
Ficheros en este ítem:
No hay ficheros asociados a este ítem.