Zobrazeno 1 - 10
of 88
pro vyhledávání: '"Markus Reiter"'
Autor:
Roland Ambros, Angelika Bernsteiner, Roderick Bloem, Dominik Dolezal, David Garcia, Katrin Göltl, Claudia Haagen-Schützenhöfer, Markus Hadler, Timotheus Hell, Alina Herderich, Petar Jercic, Fares Kayali, Ferenc Kemény, Christoph Kirsch, Beate Kloesch, Daniel Kocher, Karin Landerl, Jana Lasser, Elisabeth Lex, Renate Motschnig, Claudia Plant, Lisa Posch, Markus Reiter-Haas, Thomas Schubatzky, Wolfgang Slany, Ana Sokolova, Philipp Spitzer, Matthias Steinböck, Yllka Velaj, Pelin Yüksel-Arslan
Publikováno v:
Zeitschrift für Hochschulentwicklung, Vol 18, Iss Sonderheft Hochschullehre (2023)
This article presents a progress report from the last two years of the Teaching Digital Thinking (TDT) project. This project aims to implement new concepts, didactic methods, and teaching formats for sustainable digital transformation in Austrian Uni
Externí odkaz:
https://doaj.org/article/a38c0259a7144b61826c0648cb829e40
Publikováno v:
Frontiers in Sociology, Vol 7 (2022)
Research on combining social survey responses and social media posts has shown that the willingness to share social media accounts in surveys depends on the mode of the survey and certain socio-demographics of the respondents. We add new insights to
Externí odkaz:
https://doaj.org/article/b7bdca37449b4dc4a6ba8f2d2cf60b8a
Publikováno v:
Innovation: The European Journal of Social Science Research. :1-24
Autor:
Markus Reiter-Haas
Publikováno v:
Companion Proceedings of the ACM Web Conference 2023.
Publikováno v:
4th International Conference on Advanced Research Methods and Analytics (CARMA 2022).
This paper contributes to the research on combining public opinion surveys and social media data by a) analyzing the effects of social desirability on the willingness to provide social media account information in surveys, and b) evaluating the congr
Autor:
Elisabeth Lex, Emanuel Lacic, Junghoo Cho, Manoj Reddy Dareddy, Dominik Kowald, Markus Reiter-Haas
Publikováno v:
User Modeling and User-Adapted Interaction. 30:617-658
In this work, we address the problem of providing job recommendations in an online session setting, in which we do not have full user histories. We propose a recommendation approach, which uses different autoencoder architectures to encode sessions f
Publikováno v:
Journal of Fluid Mechanics. 936
This work addresses the effects of different thermal sidewall boundary conditions on the formation of flow states and heat transport in two- and three-dimensional Rayleigh–Bénard convection (RBC) by means of direct numerical simulations and steady
Autor:
Christof Bless, Lukas Dötlinger, Michael Kaltschmid, Markus Reiter, Anelia Kurteva, Antonio J. Roa-Valverde, Anna Fensel
Knowledge graphs facilitate systematic large-scale data analysis by providing both human and machine-readable structures, which can be shared across different domains and platforms. Nowadays, knowledge graphs can be used to standardise the collection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2659::d284c265f819976c34878df2481975b2
https://zenodo.org/record/7602446
https://zenodo.org/record/7602446
Autor:
Markus Schedl, Elisabeth Lex, Marko Tkalcic, Markus Reiter-Haas, Emilia Parada-Cabaleiro, Elham Motamedi
Publikováno v:
RecSys
Providing suitable recommendations is of vital importance to improve the user satisfaction of music recommender systems. Here, users often listen to the same track repeatedly and appreciate recommendations of the same song multiple times. Thus, accou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fea6839f71f4629ac0de25c6cecfd1c5
Autor:
Ingrid Karner, Markus Reiter
Publikováno v:
Mathematik, Sprache und Medien
Ein Blick in österreichische (Grund-)Schulklassen zeigt ein teilweise sehr heterogenes Bild hinsichtlich der Erstsprachen der Kinder. Diese Situation stellt eine große Herausforderung für jede Lehrkraft dar. An vielen österreichischen Schulen ist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fefa79747b7282c48b6b6508b914467
https://doi.org/10.37626/ga9783959871969.0.06
https://doi.org/10.37626/ga9783959871969.0.06