Pintér, Ádám and Schmuck, Balázs and Szénási, Sándor (2018) Short text evaluation with neural network. Pollack Periodica, 13 (3). pp. 107-118. ISSN 1788-1994
|
Text
606.2018.13.3.11.pdf Download (581kB) | Preview |
Abstract
The aim of this paper is to present a technique, which uses machine learning to process the short text answers with Hungarian language. The processing is based on a special neural network, the convolutional neural network, which can efficiently process short text answer. To achieve precise classification for training and recall grammatically consistent answers and the conversion of the text to the input are inevitable. To convert the input, continuous bag of words and Skip-Gram models will be used, resulting in a model that will be able to evaluate the Hungarian short text answers.
| Item Type: | Article |
|---|---|
| Subjects: | T Technology / alkalmazott, műszaki tudományok > TA Engineering (General). Civil engineering (General) / általános mérnöki tudományok |
| Depositing User: | Erika Bilicsi |
| Date Deposited: | 01 Aug 2019 09:44 |
| Last Modified: | 31 Dec 2020 00:34 |
| URI: | http://real.mtak.hu/id/eprint/95012 |
Actions (login required)
 |
Edit Item |
