Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Zaveri, Amrapali"'
The issue of climate change has become increasingly noteworthy in the past years, the transition towards a renewable energy system is a priority in the transition to a sustainable society. In this document, we explore the definition of green energy t
Externí odkaz:
http://arxiv.org/abs/2004.10562
Autor:
Zaveri, Amrapali
In recent years, the Linked Data (LD) paradigm has emerged as a simple mechanism for employing the Web as a medium for data and knowledge integration where both documents and data are linked. Moreover, the semantics and structure of the underlying da
Externí odkaz:
https://ul.qucosa.de/id/qucosa%3A13295
https://ul.qucosa.de/api/qucosa%3A13295/attachment/ATT-0/
https://ul.qucosa.de/api/qucosa%3A13295/attachment/ATT-0/
Autor:
Vissoci, Joao Ricardo Nickenig, Rodrigues, Clarissa G., de Andrade, Luciano, Santana, Jose Eduardo, Zaveri, Amrapali, Pietrobon, Ricardo
The aim of this article is to introduce a reporting framework for reproducible, interactive research applied to Big Clinical Data, based on open source technologies. The framework is constituted by the following three axes: (i) data, (ii) analytical
Externí odkaz:
http://arxiv.org/abs/1304.5688
Autor:
Grigoriu, Andreea1 (AUTHOR) a.grigoriu@maastrichtuniversity.nl, Zaveri, Amrapali1 (AUTHOR), Weiss, Gerhard2 (AUTHOR), Dumontier, Michel1 (AUTHOR)
Publikováno v:
Journal of Biomedical Semantics. 3/24/2021, Vol. 12 Issue 1, p1-12. 12p.
Autor:
Zaveri, Amrapali1 zaveri@maastrichtuniversity.nl, Ertaylan, Gökhan2 gokhan.ertaylan@maastrichtuniversity.nl
Publikováno v:
Algorithms. Dec2017, Vol. 10 Issue 4, p126. 16p.
Autor:
Zheng, Yalung, Ezeiza, Jon, Farzanehpour, Mehdi, Urbani, Jacopo, Gray, Alasdair J.G., Janowicz, Krzysztof, Hammar, Karl, Hitzler, Pascal, Fernández, Miriam, Lopez, Vanessa, Haller, Armin, Zaveri, Amrapali
Publikováno v:
The Semantic Web ISBN: 9783030213473
ESWC
Zheng, Y, Ezeiza, J, Farzanehpour, M & Urbani, J 2019, Predicting entity mentions in scientific literature . in A J G Gray, K Janowicz, K Hammar, P Hitzler, M Fernández, V Lopez, A Haller & A Zaveri (eds), The Semantic Web : 16th International Conference, ESWC 2019, Portorož, Slovenia, June 2–6, 2019, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11503 LNCS, Springer Verlag, pp. 379-393, 16th International Semantic Web Conference, ESWC 2019, Portorož, Slovenia, 2/06/19 . https://doi.org/10.1007/978-3-030-21348-0_25
The Semantic Web: 16th International Conference, ESWC 2019, Portorož, Slovenia, June 2–6, 2019, Proceedings, 379-393
STARTPAGE=379;ENDPAGE=393;TITLE=The Semantic Web
ESWC
Zheng, Y, Ezeiza, J, Farzanehpour, M & Urbani, J 2019, Predicting entity mentions in scientific literature . in A J G Gray, K Janowicz, K Hammar, P Hitzler, M Fernández, V Lopez, A Haller & A Zaveri (eds), The Semantic Web : 16th International Conference, ESWC 2019, Portorož, Slovenia, June 2–6, 2019, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11503 LNCS, Springer Verlag, pp. 379-393, 16th International Semantic Web Conference, ESWC 2019, Portorož, Slovenia, 2/06/19 . https://doi.org/10.1007/978-3-030-21348-0_25
The Semantic Web: 16th International Conference, ESWC 2019, Portorož, Slovenia, June 2–6, 2019, Proceedings, 379-393
STARTPAGE=379;ENDPAGE=393;TITLE=The Semantic Web
Predicting which entities are likely to be mentioned in scientific articles is a task with significant academic and commercial value. For instance, it can lead to monetary savings if the articles are behind paywalls, or be used to recommend articles
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae46f8d12138f9389cd62c7b4cb135be
https://research.vu.nl/en/publications/af026e99-e2a6-4c5b-88f6-5c04c849ed2f
https://research.vu.nl/en/publications/af026e99-e2a6-4c5b-88f6-5c04c849ed2f
Autor:
Wei Hu1, Zaveri, Amrapali2, Honglei Qiu1, Dumontier, Michel2 michel.dumontier@maastrichtuniversity.nl
Publikováno v:
BMC Bioinformatics. 9/18/2017, Vol. 18, p1-12. 12p. 2 Diagrams, 7 Charts, 3 Graphs.
Akademický článek
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Publikováno v:
Encyclopedia of Big Data Technologies ISBN: 9783319639628
Encyclopedia of Big Data Technologies
Encyclopedia of Big Data Technologies, 11-17
STARTPAGE=11;ENDPAGE=17;TITLE=Encyclopedia of Big Data Technologies
Encyclopedia of Big Data Technologies
Encyclopedia of Big Data Technologies, 11-17
STARTPAGE=11;ENDPAGE=17;TITLE=Encyclopedia of Big Data Technologies
In this chapter, we first introduce the concepts of Linked Data quality and its dimensions and metrics. Then we provide definitions for 18 quality dimensions along with a total of 69 metrics to measure the dimensions. Thereafter, we provide an overvi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab0f023d5e244a524a7c600786708fdb
http://hdl.handle.net/10281/228187
http://hdl.handle.net/10281/228187
Autor:
Moodley, Kody, Zaveri, Amrapali, Wu, Chunlei, Dumontier, Michel, Baker, Christopher J. O., Waagmeester, Andra, Splendiani, Andrea, Beyan, Oya Deniz, Marshall, M. Scott
Publikováno v:
Semantic Web Applications and Tools for Health Care and Life Sciences, 2275
Chemical substance resources on the Web are often made accessible to researchers through public APIs (Application Programming Interfaces). A significant problem of missing provenance information arises when extracting and integrating data in such API
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=narcis______::4a25d665319bf42ef9b7d45b4652a219
https://cris.maastrichtuniversity.nl/en/publications/08abc748-6b0b-4b78-80aa-aadfa76dda59
https://cris.maastrichtuniversity.nl/en/publications/08abc748-6b0b-4b78-80aa-aadfa76dda59