Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Amaryllis Mavragani"'
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e51584 (2023)
The ethics of generative artificial intelligence (AI) use in scientific manuscript content creation has become a serious matter of concern in the scientific publishing community. Generative AI has computationally become capable of elaborating researc
Externí odkaz:
https://doaj.org/article/90c86dbeeec241eeabe242799aec4289
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
Abstract Due to the COVID-19 pandemic originating in China in December 2019, apart from the grave concerns on the exponentially increasing casualties, the affected countries are called to deal with severe repercussions in all aspects of everyday life
Externí odkaz:
https://doaj.org/article/f10cee83a8fb4f369d5ca9a3adfc2b35
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-19 (2020)
Abstract During the last decade, the use of online search traffic data is becoming popular in examining, analyzing, and predicting human behavior, with Google Trends being a popular tool in monitoring and analyzing the users' online search patterns i
Externí odkaz:
https://doaj.org/article/cc41fa4004894847b0ae33334eab819a
Publikováno v:
Journal of Big Data, Vol 6, Iss 1, Pp 1-20 (2019)
Abstract In addressing the challenge of Big Data Analytics, what has been of notable significance is the analysis of online search traffic data in order to analyze and predict human behavior. Over the last decade, since the establishment of the most
Externí odkaz:
https://doaj.org/article/0512600322ff48aa9b14dc652dd26cb8
Autor:
Amaryllis Mavragani, Gabriela Ochoa
Publikováno v:
Journal of Big Data, Vol 5, Iss 1, Pp 1-23 (2018)
Abstract Big Data Analytics have become an integral part of Health Informatics over the past years, with the analysis of Internet data being all the more popular in health assessment in various topics. In this study, we first examine the geographical
Externí odkaz:
https://doaj.org/article/0878aa724aee4812a7b378cf310a6ac9
Autor:
Amaryllis Mavragani, Gabriela Ochoa
Publikováno v:
Journal of Big Data, Vol 5, Iss 1, Pp 1-21 (2018)
Abstract Over the past decade and with the increasing use of the Internet, the assessment of health issues using online search traffic data has become an integral part of Health Informatics. Internet data in general and from Google Trends in particul
Externí odkaz:
https://doaj.org/article/164555db8dca4a1fadfcb471cc701e1a
Publikováno v:
Mathematics, Vol 8, Iss 12, p 2255 (2020)
This paper examines the role of non-cash flow factors over correlation jumps in financial markets. Utilizing time-varying risk aversion measure as a proxy for investor sentiment and the cross-quantilogram method applied to intraday data, we show that
Externí odkaz:
https://doaj.org/article/7523c42464774f2eb1cfa6163841f745
Publikováno v:
Water, Vol 8, Iss 11, p 542 (2016)
Due to the increased interest in micropollutants, this paper aims at quantifying and analyzing the UK online interest in Diclofenac, Estradiol, Azithromycin, Clarithromycin, and Erythromycin, substances included in the EU watchlist for monitoring, in
Externí odkaz:
https://doaj.org/article/63eafaf2a21848d2b701a06ff6a0e610
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-19 (2020)
Journal of Big Data
Journal of Big Data
During the last decade, the use of online search traffic data is becoming popular in examining, analyzing, and predicting human behavior, with Google Trends being a popular tool in monitoring and analyzing the users' online search patterns in several
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0df332dc86fae215ad861fa435791fe
http://link.springer.com/article/10.1186/s40537-020-00337-2
http://link.springer.com/article/10.1186/s40537-020-00337-2
Publikováno v:
Mathematics, Vol 8, Iss 2255, p 2255 (2020)
Mathematics
Volume 8
Issue 12
Mathematics
Volume 8
Issue 12
This paper examines the role of non-cash flow factors over correlation jumps in financial markets. Utilizing time-varying risk aversion measure as a proxy for investor sentiment and the cross-quantilogram method applied to intraday data, we show that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97317b879d21220a0e092bd564ed8c57
https://www.mdpi.com/2227-7390/8/12/2255
https://www.mdpi.com/2227-7390/8/12/2255