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Automatic generation of a large dictionary with concreteness/abstractness ratings based on a small human dictionary.
- Source :
- Journal of Intelligent & Fuzzy Systems; 2022, Vol. 42 Issue 5, p4513-4521, 9p
- Publication Year :
- 2022
-
Abstract
- Concrete/abstract words are used in a growing number of psychological and neurophysiological research. For a few languages, large dictionaries have been created manually. This is a very time-consuming and costly process. To generate large high-quality dictionaries of concrete/abstract words automatically one needs extrapolating the expert assessments obtained on smaller samples. The research question that arises is how small such samples should be to do a good enough extrapolation. In this paper, we present a method for automatic ranking concreteness of words and propose an approach to significantly decrease amount of expert assessment. The method has been evaluated on a large test set for English. The quality of the constructed dictionaries is comparable to the expert ones. The correlation between predicted and expert ratings is higher comparing to the state-of-the-art methods. [ABSTRACT FROM AUTHOR]
- Subjects :
- ENCYCLOPEDIAS & dictionaries
PSYCHOLOGICAL research
EXTRAPOLATION
Subjects
Details
- Language :
- English
- ISSN :
- 10641246
- Volume :
- 42
- Issue :
- 5
- Database :
- Complementary Index
- Journal :
- Journal of Intelligent & Fuzzy Systems
- Publication Type :
- Academic Journal
- Accession number :
- 156139433
- Full Text :
- https://doi.org/10.3233/JIFS-219240