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ORCID: https://orcid.org/0000-0003-3877-0089 and Minker, Wolfgang
(2012).
Investigating verbal intelligence using the TF-IDF approach.
En: "LREC 2012, Eighth International Conference on Language Resources and Evaluation", 21/05/2012 - 27/05/2013, Istanbul. ISBN 978-2-9517408-7-7. pp. 1573-1576.
| Título: | Investigating verbal intelligence using the TF-IDF approach |
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| Autor/es: |
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| Tipo de Documento: | Ponencia en Congreso o Jornada (Artículo) |
| Título del Evento: | LREC 2012, Eighth International Conference on Language Resources and Evaluation |
| Fechas del Evento: | 21/05/2012 - 27/05/2013 |
| Lugar del Evento: | Istanbul |
| Título del Libro: | Proceedings of LREC 2012, Eighth International Conference on Language Resources and Evaluation |
| Fecha: | Mayo 2012 |
| ISBN: | 978-2-9517408-7-7 |
| Materias: | |
| ODS: | |
| Palabras Clave Informales: | Verbal intelligence, cosine similarity, TF-IDF measures |
| Escuela: | E.T.S.I. Telecomunicación (UPM) |
| Departamento: | Ingeniería Electrónica |
| Licencias Creative Commons: | Reconocimiento - Sin obra derivada - No comercial |
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In this paper we investigated differences in language use of speakers yielding different verbal intelligence when they describe the same event. The work is based on a corpus containing descriptions of a short film and verbal intelligence scores of the speakers. For analyzing the monologues and the film transcript, the number of reused words, lemmas, n-grams, cosine similarity and other features were calculated and compared to each other for different verbal intelligence groups. The results showed that the similarity of monologues of higher verbal intelligence speakers was greater than of lower and average verbal intelligence participants. A possible explanation of this phenomenon is that candidates yielding higher verbal intelligence have a better short-term memory. In this paper we also checked a hypothesis that differences in vocabulary of speakers yielding different verbal intelligence are sufficient enough for good classification results. For proving this hypothesis, the Nearest Neighbor classifier was trained using TF-IDF vocabulary measures. The maximum achieved accuracy was 92.86%.
| ID de Registro: | 20424 |
|---|---|
| Identificador DC: | https://oa.upm.es/20424/ |
| Identificador OAI: | oai:oa.upm.es:20424 |
| URL Oficial: | http://www.lrec-conf.org/proceedings/lrec2012/pdf/... |
| Depositado por: | Memoria Investigacion |
| Depositado el: | 05 Oct 2013 10:42 |
| Ultima Modificación: | 16 Dic 2024 08:46 |
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