Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Hrvoje Ljubić"'
Publikováno v:
Tehnički Vjesnik, Vol 28, Iss 3, Pp 739-745 (2021)
In this paper, a novel approach to automatic question generation (AQG) using semantic role labeling (SRL) for morphologically rich languages is presented. A model for AQG is developed for our native speaking language, Croatian. Croatian language is a
Externí odkaz:
https://doaj.org/article/640f359877164ed6bbdf8045266dac20
Publikováno v:
Tehnički Vjesnik, Vol 28, Iss 3, Pp 739-745 (2021)
Tehnički vjesnik
Volume 28
Issue 3
Tehnički vjesnik
Volume 28
Issue 3
In this paper, a novel approach to automatic question generation (AQG) using semantic role labeling (SRL) for morphologically rich languages is presented. A model for AQG is developed for our native speaking language, Croatian. Croatian language is a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d259e4d283432bba887e3ff8e5db1a1c
https://hrcak.srce.hr/file/375247
https://hrcak.srce.hr/file/375247
Publikováno v:
Lecture Notes in Networks and Systems ISBN: 9783030900540
In this article state of the art semantic role labeling (SRL) tools have been compared on published lexical resources and custom hand annotated previously unseen texts. Semantic role labeling is one of the first steps into understanding the meaning o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fca520b888b94a065838ea82d6764478
https://doi.org/10.1007/978-3-030-90055-7_16
https://doi.org/10.1007/978-3-030-90055-7_16
Autor:
Tomislav Volarić, Hrvoje Ljubić
Publikováno v:
SoftCOM
Visualization of data in learning management systems became essential for easier analysis of learner's behavior and interpretation of results on such system. In this paper, we presented design and development process of dashboard for the prototype of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9e7cde7e8da6e67ce146b8c2d25e5499
https://doi.org/10.23919/softcom.2017.8115555
https://doi.org/10.23919/softcom.2017.8115555