Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.creator | Mutlu, Belgin | - |
| dc.creator | Veas, Eduardo Enrique | - |
| dc.creator | Trattner, Christoph | - |
| dc.creator | Sabol, Vedran | - |
| dc.date | 2018-09-12T20:44:30Z | - |
| dc.date | 2018-09-12T20:44:30Z | - |
| dc.date | 2015-06 | - |
| dc.date | 2018-09-12T13:59:20Z | - |
| dc.date.accessioned | 2019-04-29T15:49:23Z | - |
| dc.date.available | 2019-04-29T15:49:23Z | - |
| dc.date.issued | 2015-06 | - |
| dc.identifier | Mutlu, Belgin; Veas, Eduardo Enrique; Trattner, Christoph; Sabol, Vedran; Towards a Recommender Engine for Personalized Visualizations; Springer; Lecture Notes in Computer Science; 9146; 6-2015; 169-182 | - |
| dc.identifier | 0302-9743 | - |
| dc.identifier | http://hdl.handle.net/11336/59455 | - |
| dc.identifier | CONICET Digital | - |
| dc.identifier | CONICET | - |
| dc.identifier.uri | http://rodna.bn.gov.ar:8080/jspui/handle/bnmm/302975 | - |
| dc.description | Visualizations have a distinctive advantage when dealing with the information overload problem: since they are grounded in basic visual cognition, many people understand them. However, creating them requires specific expertise of the domain and underlying data to determine the right representation. Although there are rules that help generate them, the results are too broad to account for varying user preferences. To tackle this issue, we propose a novel recommender system that suggests visualizations based on (i) a set of visual cognition rules and (ii) user preferences collected in Amazon-Mechanical Turk. The main contribution of this paper is the introduction and the evaluation of a novel approach called VizRec that can suggest an optimal list of top-n visualizations for heterogeneous data sources in a personalized manner. | - |
| dc.description | Fil: Mutlu, Belgin. Know-Center GmbH; Austria | - |
| dc.description | Fil: Veas, Eduardo Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Know-Center GmbH; Austria | - |
| dc.description | Fil: Trattner, Christoph. Know-Center GmbH; Austria | - |
| dc.description | Fil: Sabol, Vedran. Know-Center GmbH; Austria | - |
| dc.format | application/pdf | - |
| dc.format | application/pdf | - |
| dc.language | eng | - |
| dc.publisher | Springer | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1007/978-3-319-20267-9_14 | - |
| dc.relation | info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/chapter/10.1007/978-3-319-20267-9_14 | - |
| 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 | COLLABORATIVE FILTERING | - |
| dc.subject | CROWD-SOURCING | - |
| dc.subject | PERSONALIZED VISUALIZATIONS | - |
| dc.subject | RECOMMENDER SYSTEMS | - |
| dc.subject | VISUALIZATION RECOMMENDER | - |
| dc.subject | Ciencias de la Computación | - |
| dc.subject | Ciencias de la Computación e Información | - |
| dc.subject | CIENCIAS NATURALES Y EXACTAS | - |
| dc.title | Towards a Recommender Engine for Personalized Visualizations | - |
| 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 | |
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