| 1. |
- Dritsa, Konstantina, et al.
(författare)
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A Greek Parliament Proceedings Dataset for Computational Linguistics and Political Analysis
- 2022
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Konferensbidrag (refereegranskat)abstract
- Large, diachronic datasets of political discourse are hard to come across, especially for resource-lean languages such as g In this paper, we introduce a curated dataset of the Greek Parliament Proceedings that extends chronologically from 1989 up to 2020. It consists of more than 1 million speeches with extensive metadata, extracted from 5,355 parliamentary record files. We explain how it was constructed and the challenges that we had to overcome. The dataset can be used for both computational linguistics and political analysis—ideally, combining the two. We present such an application, showing (i) how the dataset can be used to study the change of word usage through time, (ii) between significant historical events and political parties, (iii) by evaluating and employing algorithms for detecting semantic shifts.
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| 2. |
- Lagkiou, Konstantina, et al.
(författare)
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Distant Viewing of Ukiyo-e Prints
- 2022
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Ingår i: Proceedings of the Thirteenth Language Resources and Evaluation Conference. - Marseilles : European Language Resources Association. ; , s. 5879-5888
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Konferensbidrag (refereegranskat)abstract
- This paper contributes to studying relationships between Japanese topography and places featured in early modern landscape prints, so-called ukiyo-e or ‘pictures of the floating world’. The printed inscriptions on these images feature diverse place-names, both man-made and natural formations. However, due to the corpus’s richness and diversity, the precise nature of artistic mediation of the depicted places remains little understood. In this paper, we explored a new analytical approach based on the macroanalysis of images facilitated by Natural Language Processing technologies. This paper presents a small dataset with inscriptions on prints that have been annotated by an art historian for included place-name entities. Our dataset is released for public use. By fine-tuning and applying a Japanese BERT-based Name Entity Recogniser, we provide a use-case of a macroanalysis of a visual dataset that is hosted by the digital database of the Art Research Center at the Ritsumeikan University, Kyoto. Our work studies the relationship between topography and its visual renderings in early modern Japanese ukiyo-e landscape prints, demonstrating how an art historian’s work can be improved with Natural Language Processing toward distant viewing of visual datasets.
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| 3. |
- Pavlopoulos, John, et al.
(författare)
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Diagnostic captioning : a survey
- 2022
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Ingår i: Knowledge and Information Systems. - : Springer Science and Business Media LLC. - 0219-1377 .- 0219-3116. ; 64:7, s. 1691-1722
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Tidskriftsartikel (refereegranskat)abstract
- Diagnostic captioning (DC) concerns the automatic generation of a diagnostic text from a set of medical images of a patient collected during an examination. DC can assist inexperienced physicians, reducing clinical errors. It can also help experienced physicians produce diagnostic reports faster. Following the advances of deep learning, especially in generic image captioning, DC has recently attracted more attention, leading to several systems and datasets. This article is an extensive overview of DC. It presents relevant datasets, evaluation measures, and up-to-date systems. It also highlights shortcomings that hinder DC’s progress and proposes future directions.
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