Linking IMAGACT ontology to BabelNet through action videos

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July 26, 2017

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OpenEdition


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Computational Linguistics natural language experimental methodologies Linguistica Computazionale linguaggio naturale metodologie sperimentali Linguistique Computationelle langage naturel méthodes expérimentales LAW009000 Language & Linguistics (General) LNP

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Videorecordings Videos Being

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Lorenzo Gregori et al., « Linking IMAGACT ontology to BabelNet through action videos », Accademia University Press, ID : 10.4000/books.aaccademia.1785


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Abstract En It

Herein we present a study dealing with the linking of two multilingual and multimedia resources, BabelNet and IMAGACT, which seeks to connect videos contained in the IMAGACT Ontology of Actions with related action concepts in BabelNet. The linking is based on a machine learning algorithm that exploits the lexical information of the two resources. The algorithm has been firstly trained and tested on a manually annotated dataset and then it was run on all the data, allowing to connect 773 IMAGACT action videos with 517 BabelNet synsets. This linkage aims to enrich BabelNet verbal entries with a visual representations and to connect the IMAGACT ontology to the huge BabelNet semantic network.

In questo articolo si presenta uno studio sul linking tra due risorse linguistiche multilingui e multimediali, BabelNet e IMAGACT. L’esperimento ha l’obiettivo di collegare i video dell’ontologia dell’azione IMAGACT con i concetti azionali contenuti in BabelNet. Il collegamento è realizzato attraverso un algoritmo di Machine Learning che sfrutta l’informazione lessicale delle due risorse. L’algoritmo è stato addestrato e valutato su un dataset annotato manualmente e poi eseguito sull’insieme totale dei dati, permettendo di collegare 773 video di IMAGACT con 517 synset di BabelNet. Questo linking ha lo scopo di arricchire le entrate verbali di BabelNet con una rappresentazione visuale e di collegare IMAGACT alla rete semantica di BabelNet.

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