A complementary account to emotion extraction and classification in cultural heritage based on the Plutchik's theory

Andrea Bolioli, Alessio Bosca, Rossana Damiano, Antonio Lieto, Manuel Striani

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Abstract

The paper presents a combined approach to knowledge-based emotion attribution and classification of cultural items employed in the H2020 project SPICE. In particular, we show a preliminary experimentation conducted on a selection of items contributed by the GAM Museum in Turin (Galleria di Arte Moderna), pointing out how different language-based approaches to emotion categorization (used in the systems Sophia and DEGARI respectively) can be powerfully combined to cope with both coverage and extended affective attributions. Interestingly, both approaches are based on an ontology of the Plutchik's theory of emotions.

Lingua originaleInglese
Titolo della pubblicazione ospiteUMAP2022 - Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
EditoreAssociation for Computing Machinery, Inc
Pagine374-382
Numero di pagine9
ISBN (elettronico)9781450392327
DOI
Stato di pubblicazionePubblicato - 4 lug 2022
Pubblicato esternamente
Evento30th ACM Conference on User Modeling, Adaptation and Personalization, UMAP2022 - Virtual, Online, Spain
Durata: 4 lug 20227 lug 2022

Serie di pubblicazioni

NomeUMAP2022 - Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization

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???event.eventtypes.event.conference???30th ACM Conference on User Modeling, Adaptation and Personalization, UMAP2022
Paese/TerritorioSpain
CittàVirtual, Online
Periodo4/07/227/07/22

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