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- Santini, Marina, 1960-, et al.
(author)
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Designing an Extensible Domain-Specific Web Corpus for “Layfication” : A Case Study in eCare at Home : Chapter 6
- 2019
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In: Cyber-Physical Systemsfor Social Applications. - Hershey PA, USA 17033 : Engineering Science Reference. - 9781522578796 - 9781522578802 ; , s. 98-155
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Book chapter (other academic/artistic)abstract
- In the era of data-driven science, corpus-based language technology is an essential part of cyber physicalsystems. In this chapter, the authors describe the design and the development of an extensible domainspecificweb corpus to be used in a distributed social application for the care of the elderly at home.The domain of interest is the medical field of chronic diseases. The corpus is conceived as a flexible andextensible textual resource, where additional documents and additional languages will be appendedover time. The main purpose of the corpus is to be used for building and training language technologyapplications for the “layfication” of the specialized medical jargon. “Layfication” refers to the automaticidentification of more intuitive linguistic expressions that can help laypeople (e.g., patients, familycaregivers, and home care aides) understand medical terms, which often appear opaque. Exploratoryexperiments are presented and discussed.
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2. |
- Santini, Marina, 1960-, et al.
(author)
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Introducing the notion of ‘contrast’ features for language technology
- 2019
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In: International Conference on Database and Expert Systems Applications DEXA 2019: Database and Expert Systems Applications. - Cham : Springer Verlag. ; , s. 189-198, s. 189-198
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Conference paper (peer-reviewed)abstract
- In this paper, we explore whether there exist ‘contrast’ features that help recognize if a text variety is a genre or a domain. We carry out our experiments on the text varieties that are included in the Swedish national corpus, called Stockholm-Umeå Corpus or SUC, and build several text classification models based on text complexity features, grammatical features, bag-of-words features and word embeddings. Results show that text complexity features and grammatical features systematically perform better on genres rather than on domains. This indicates that these features can be used as ‘contrast’ features because, when in doubt about the nature of a text category, they help bring it to light.
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