Pregled bibliografske jedinice broj: 1145561
An Analysis of Early Use of Deep Learning Terms in Natural Language Processing
An Analysis of Early Use of Deep Learning Terms in Natural Language Processing // 43nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2020)
Opatija: Institute of Electrical and Electronics Engineers (IEEE), 2020. str. 1125-1130 doi:10.23919/MIPRO48935.2020.9245375 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
An Analysis of Early Use of Deep Learning Terms in
Natural Language Processing
Autori
Dalbelo Bašić, Bojana ; di Buono ; Maria
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Skup
43nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2020)
Mjesto i datum
Opatija, Hrvatska, 28.09.2020. - 02.10.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
NLP, deep learning, correspondence analysis
Sažetak
N this paper, we present the preliminary results on the analysis of deep learning terms used for natural language processing (NLP) tasks. We propose a statistical analysis of papers published from 2012 to 2015 in the main ACL conferences. Our aim is investigating which DL term, and consequently which DL method, is mostly used for each specific NLP task, since its introduction in the field. In order to do this, our first contribution is the development of two terminological lists, referring respectively to DL methods for text analysis and NLP tasks. The list of deep learning terms contains 41 terms and acronyms, as well as a NLP term list contains 145 terms and acronyms. From our corpus, the frequencies of various terms have been extracted with respect to the ACL conference and the publication year. After the preliminary data analysis, we decided to restrict the extraction process to abstract texts. We applied multivariate techniques called correspondence analysis in order to visualize and evaluate the joint behavior of our variables.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb