Automatic Analysis of Dreams

Automatic Analysis of Dreams

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dc.contributor.author Amini, Reza
dc.date.accessioned 2011-10-05T20:15:57Z
dc.date.available 2011-10-05T20:15:57Z
dc.date.created 2011 en_US
dc.date.issued 2011-10-05
dc.identifier.uri http://hdl.handle.net/10393/20290
dc.description.abstract In a scientific study of dream content, artificial intelligence has been utilized to automatically score dream content. An initial attempt focused on scoring for emotional tone of dream reports. The contribution of this thesis demonstrates methods by which accuracy of such a system can be improved beyond text-mining. It was hypothesized that data extraction based on psychological processes will provide significant information that would produce an accurate model. In our first article, the significance of words expressed in dream reports, along with their associated words was explored. Extraction and inclusion of these associations provided detailed information that improved automatic scoring of positive and negative affect even though these associations exhibited skewed distribution. The second article demonstrated how normalization of the data was possible and how it could result in a more accurate model. Our last article was able to demonstrate that the model can differentiate between male and female dreams. en_US
dc.language.iso en en_US
dc.subject Emotions en_US
dc.subject Dreams en_US
dc.subject Automatic Analysis en_US
dc.subject Artificial Intelligence en_US
dc.title Automatic Analysis of Dreams en_US
dc.type Thèse / Thesis en_US
dc.faculty.department Psychologie / Psychology en_US
dc.contributor.supervisor De Koninck, Joseph
dc.embargo.terms immediate en_US
dc.degree.name MA en_US
dc.degree.level masters en_US
dc.degree.discipline Sciences sociales / Social Sciences en_US

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