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@proceedings{1347766,
author = {Komenda, Martin and Víta, Martin and Karolyi, Matěj and Kríž, Vincent and Pokorná, Andrea},
keywords = {Curriculum mapping; word2vec; medical and healthcare education; similarity analysis},
language = {eng},
title = {Word2vec in practice: A similarity analysis of medical and healthcare disciplines},
year = {2016}
}
TY - CONF
ID - 1347766
AU - Komenda, Martin - Víta, Martin - Karolyi, Matěj - Kríž, Vincent - Pokorná, Andrea
PY - 2016
TI - Word2vec in practice: A similarity analysis of medical and healthcare disciplines
KW - Curriculum mapping
KW - word2vec
KW - medical and healthcare education
KW - similarity analysis
N2 - Modern high-quality education is based on guaranteed, structured and well-balanced curricula covering the necessary scope of knowledge and skills required in subsequent practice, which respond to changing epidemiological profiles, health systems challenges and population health needs. The general idea is to obtain vector representations of words included in descriptions of disciplines, represent the textual content in a vector space (word2vec in particular) and visualise the results of similarity analysis as an interactive web-based report. We present the findings of the real application of the word2vec approach on curriculum data and reflect on its implications in the long-term process of curriculum innovation. The paper describes an appealing way of exploring that can be helpful to anyone who is involved in the complicated and time-consuming process of curriculum design at institutions of higher education. The final visual report serves as a comprehensive overview on selected parts of curriculum described in each discipline in order to provide transparent data for further evaluation.
ER -
KOMENDA, Martin, Martin VÍTA, Matěj KAROLYI, Vincent KRÍŽ a Andrea POKORNÁ. \textit{Word2vec in practice: A similarity analysis of medical and healthcare disciplines}. 2016.
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