Christine Bauer
Christine Bauer
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Article-Journal
EXID: Development and Validation of the Experienced Impact of Disruptions Scale
Disruptions in public transport can significantly affect how travelers experience their journeys. While several attempts have been made …
Marloes Vredenborg
,
Marit Bentvelzen
,
Anouk Van Kasteren
,
Christine Bauer
,
Judith Masthoff
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JIF 2024: 4.4
VHB 2024: B
Where are the values? A systematic literature review on news recommender systems
In the recommender systems field, it is increasingly recognized that focusing on accuracy measures is limiting and misguided. …
Christine Bauer
,
Chandni Bagchi
,
Olusanmi A. Hundogan
,
Karin Van Es
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Project
Video
DOI
ACM Author-izer
Women in RecSys Journal Paper of the Year Award 2024, Senior category
Exploring the landscape of recommender systems evaluation: practices and perspectives
Recommender systems research and practice are fast-developing topics with growing adoption in a wide variety of information access …
Christine Bauer
,
Eva Zangerle
,
Alan Said
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Project
Poster
DOI
ACM Author-izer
Introduction to the Special Issue on Perspectives on Recommender Systems Evaluation
Evaluation plays a vital role in recommender systems—in research and practice—whether for confirming algorithmic concepts or assessing …
Christine Bauer
,
Eva Zangerle
,
Alan Said
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Project
DOI
ACM Author-izer
Intra-list similarity and human diversity perceptions of recommendations: the details matter
The diversity of the generated item suggestions can be an important quality factor of a recommender system. In offline experiments, …
Mathias Jesse
,
Christine Bauer
,
Dietmar Jannach
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DOI
Code
JIF 2024: 3.5
CORE 2020: A
Evaluating recommender systems: survey and framework
The comprehensive evaluation of the performance of a recommender system is a complex endeavor: many facets need to be considered in …
Eva Zangerle
,
Christine Bauer
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Project
Video
DOI
ACM Author-izer
JIF 2024: 28
CORE 2020: A*
VHB 2024: A
Women in RecSys Journal Paper of the Year Award 2023, Senior category
Fairness in music recommender systems: a stakeholder-centered mini review
The performance of recommender systems highly impacts both music streaming platform users and the artists providing music. As fairness …
Karlijn Dinnissen
,
Christine Bauer
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Project
DOI
JIF 2024: 2.3
Listener modeling and context-aware music recommendation based on country archetypes
Music preferences are strongly shaped by the cultural and socio-economic background of the listener, which is reflected, to a …
Markus Schedl
,
Christine Bauer
,
Wolfgang Reisinger
,
Dominik Kowald
,
Elisabeth Lex
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Project
DOI
Material:
JIF 2024: 4.7
VHB 2024: C
Support the underground: characteristics of beyond-mainstream music listeners
Music recommender systems have become an integral part of music streaming services such as Spotify and Last.fm to assist users …
Dominik Kowald
,
Peter Müllner
,
Eva Zangerle
,
Christine Bauer
,
Markus Schedl
,
Elisabeth Lex
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Project
DOI
Code
Material:
JIF 2024: 2.5
Escaping the McNamara Fallacy: toward more impactful recommender systems research
Recommender systems are among today’s most successful application areas of artificial intelligence. However, in the recommender systems …
Dietmar Jannach
,
Christine Bauer
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DOI
Postprint
JIF 2024: 3.2
CORE 2020: C
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