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AMBIENTUM BIOETHICA BIOLOGIA CHEMIA DIGITALIA DRAMATICA EDUCATIO ARTIS GYMNAST. ENGINEERING EPHEMERIDES EUROPAEA GEOGRAPHIA GEOLOGIA HISTORIA HISTORIA ARTIUM INFORMATICA IURISPRUDENTIA MATHEMATICA MUSICA NEGOTIA OECONOMICA PHILOLOGIA PHILOSOPHIA PHYSICA POLITICA PSYCHOLOGIA-PAEDAGOGIA SOCIOLOGIA THEOLOGIA CATHOLICA THEOLOGIA CATHOLICA LATIN THEOLOGIA GR.-CATH. VARAD THEOLOGIA ORTHODOXA THEOLOGIA REF. TRANSYLVAN
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The STUDIA UNIVERSITATIS BABEŞ-BOLYAI issue article summary The summary of the selected article appears at the bottom of the page. In order to get back to the contents of the issue this article belongs to you have to access the link from the title. In order to see all the articles of the archive which have as author/co-author one of the authors mentioned below, you have to access the link from the author's name. |
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STUDIA INFORMATICA - Issue no. 2 / 2022 | |||||||
Article: |
EXTENDED MAMMOGRAM CLASSIFICATION FROM TEXTURAL FEATURES. Authors: ADÉL BAJCSI, CAMELIA CHIRA, ANCA ANDREICA. |
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Abstract: DOI: 10.24193/subbi.2022.2.01 Published Online: 2023-02-06 pp. 5-20 VIEW PDF FULL PDF In the culture of the present emojis play an important role in written/typed communication, having a primary role of supplementing the words with emotional cues. While in different cultures emojis can be interpreted and thus used differently, a small set of emojis have clear meaning and strong sentiment polarity. In this work we study how to map natural language texts to emoji sequences, more precisely, we automatically assign emojis to movie subtitles/scripts. The pipeline of the proposed method is as follows: first the most relevant words are extracted from the movie subtitle, and then these are mapped to emojis. In order to perform the mapping, three methods are proposed: a lexical matching-based, a word embedding-based and a combined approach. To demonstrate the viability of the approach, we list some of the generated emojis for a randomly selected movie subset, showing also the deficiencies of the method in generating guessable sequences. Evaluation is performed via quizzes completed by human participants. Received by the editors: 20 September 2022. 2010 Mathematics Subject Classification. 68T35. 1998 CR Categories and Descriptors. I.2.1 [Artifical Intelligence]: Applications and Expert Systems – Medicine and science; I.2.6 [Artifical Intelligence]: Learning – Knowledge acquisition; I.4.7 [Image Processing and Computer Vision]: Feature Measurement – Feature representation; Key words and phrases. Breast cancer detection, Mammogram classification, GLRLM, Feature selection, Random Forests, MIAS, DDSM. |
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