Artículo
The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text
Fecha de publicación:
11/2017
Editorial:
Elsevier
Revista:
Consciousness and Cognition
ISSN:
1053-8100
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
Computer-based dreams content analysis relies on word frequencies within predefined categories in order to identify different elements in text. As a complementary approach, we explored the capabilities and limitations of word-embedding techniques to identify word usage patterns among dream reports. These tools allow us to quantify words associations in text and to identify the meaning of target words. Word-embeddings have been extensively studied in large datasets, but only a few studies analyze semantic representations in small corpora. To fill this gap, we compared Skip-gram and Latent Semantic Analysis (LSA) capabilities to extract semantic associations from dream reports. LSA showed better performance than Skip-gram in small size corpora in two tests. Furthermore, LSA captured relevant word associations in dream collection, even in cases with low-frequency words or small numbers of dreams. Word associations in dreams reports can thus be quantified by LSA, which opens new avenues for dream interpretation and decoding.
Palabras clave:
Dream Content Analysis
,
Latent Semantic Analysis
,
Word2vec
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Identificadores
Colecciones
Articulos(OCA CIUDAD UNIVERSITARIA)
Articulos de OFICINA DE COORDINACION ADMINISTRATIVA CIUDAD UNIVERSITARIA
Articulos de OFICINA DE COORDINACION ADMINISTRATIVA CIUDAD UNIVERSITARIA
Citación
Altszyler Lemcovich, Edgar Jaim; Ribeiro, Sidarta; Sigman, Mariano; Fernandez Slezak, Diego; The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text; Elsevier; Consciousness and Cognition; 56; 11-2017; 178-187
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