Christine Bauer
Christine Bauer
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Music Recommender Systems
An analysis of global and regional mainstreaminess for personalized music recommender systems
The
music mainstreaminess of a listener
reflects how strong a person’s listening preferences correspond to those of the larger …
Markus Schedl
,
Christine Bauer
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Project
DOI
CORE 2020: C
On the importance of considering country-specific aspects on the online-market: an example of music recommendation considering country-specific mainstream
In the field of music recommender systems, country-specific aspects have received little attention, although it is known that music …
Christine Bauer
,
Markus Schedl
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Project
Slides
DOI
JOURQUAL3: C
VHB 2024: B
GGS 2021: A
Introducing global and regional mainstreaminess for improving personalized music recommendation
The
music mainstreaminess of a user
reflects how strong a user’s listening preferences correspond to those of the larger …
Markus Schedl
,
Christine Bauer
PDF
Cite
Project
Slides
DOI
ACM Author-izer
CORE 2023: C
Best Paper Award
Online music listening culture of kids and adolescents: listening analysis and music recommendation tailored to the young
In this paper, we analyze a large dataset of user-generated music listening events from Last.fm, focusing on users aged 6 to 18 years. …
Markus Schedl
,
Christine Bauer
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Project
Slides
Distance- and rank-based music mainstreaminess measurement
A music listener’s mainstreaminess indicates the extent to which her listening preferences correspond to those of the population …
Markus Schedl
,
Christine Bauer
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Project
DOI
ACM Author-izer
Fine-grained culture-aware music recommender systems
This FWF-funded project (2017–2020) aimed to design and implement music recommender systems that are able to meet those requirements by considering different granularity levels of cultural aspects in a comprehensive way.
Project meta-data
Project website at CP@JKU
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