scholarly journals User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues

2020 ◽  
Vol 3 (1) ◽  
pp. 1-16
Author(s):  
Eva Zangerle ◽  
Martin Pichl ◽  
Markus Schedl
Keyword(s):  
Music Recommendation ◽  
User Models ◽  
Cultural Cues

Music Recommendation by Modeling User's Preferred Perspectives of Content, Singer/Genre and Popularity

2011 ◽  
pp. 203-221 ◽  
Author(s):  
Zehra Cataltepe ◽  
Berna Altinel
Keyword(s):  
Demographic Data ◽  
Recommendation Systems ◽  
Personal Data ◽  
Music Recommendation ◽  
Music Preferences ◽  
User Models ◽  
Online Music ◽  
Important Field ◽  
Case Based

As the amount, availability, and use of online music increase, music recommendation becomes an important field of research. Collaborative, content-based and case-based recommendation systems and their hybrids have been used for music recommendation. There are already a number of online music recommendation systems. Although specific user information, such as, demographic data, education, and origin have been shown to affect music preferences, they are usually not collected by the online music recommendation systems, because users would not like to disclose their personal data. Therefore, user models mostly contain information about which music pieces a user liked and which ones s/he did not and when.

scholarly journals Listener Modeling and Context-Aware Music Recommendation Based on Country Archetypes

2021 ◽  
Vol 3 ◽  
Author(s):  
Markus Schedl ◽  
Christine Bauer ◽  
Wolfgang Reisinger ◽  
Dominik Kowald ◽  
Elisabeth Lex
Keyword(s):  
Recommendation System ◽  
State Of The Art ◽  
Music Listening ◽  
Context Aware ◽  
Music Recommendation ◽  
Music Preferences ◽  
User Models ◽  
Gating Mechanism ◽  
Country Clusters ◽  
Country Specific

Music preferences are strongly shaped by the cultural and socio-economic background of the listener, which is reflected, to a considerable extent, in country-specific music listening profiles. Previous work has already identified several country-specific differences in the popularity distribution of music artists listened to. In particular, what constitutes the “music mainstream” strongly varies between countries. To complement and extend these results, the article at hand delivers the following major contributions: First, using state-of-the-art unsupervized learning techniques, we identify and thoroughly investigate (1) country profiles of music preferences on the fine-grained level of music tracks (in contrast to earlier work that relied on music preferences on the artist level) and (2) country archetypes that subsume countries sharing similar patterns of listening preferences. Second, we formulate four user models that leverage the user’s country information on music preferences. Among others, we propose a user modeling approach to describe a music listener as a vector of similarities over the identified country clusters or archetypes. Third, we propose a context-aware music recommendation system that leverages implicit user feedback, where context is defined via the four user models. More precisely, it is a multi-layer generative model based on a variational autoencoder, in which contextual features can influence recommendations through a gating mechanism. Fourth, we thoroughly evaluate the proposed recommendation system and user models on a real-world corpus of more than one billion listening records of users around the world (out of which we use 369 million in our experiments) and show its merits vis-à-vis state-of-the-art algorithms that do not exploit this type of context information.

scholarly journals The Origins of Religious Disbelief: A Dual Inheritance Approach

2021 ◽  
pp. 194855062199400 ◽  
Author(s):  
Will M. Gervais ◽  
Maxine B. Najle ◽  
Nava Caluori
Keyword(s):  
Cultural Transmission ◽  
Religious Commitment ◽  
Data Set ◽  
Cognitive Reflection ◽  
Theoretical Approaches ◽  
Cultural Exposure ◽  
Theories Of Religion ◽  
Nationally Representative ◽  
Cultural Cues ◽  
Dual Inheritance

Widespread religious disbelief represents a key testing ground for theories of religion. We evaluated the predictions of three prominent theoretical approaches—secularization, cognitive byproduct, and dual inheritance—in a nationally representative (United States, N = 1,417) data set with preregistered analyses and found considerable support for the dual inheritance perspective. Of key predictors of religious disbelief, witnessing fewer credible cultural cues of religious commitment was the most potent, β = .28, followed distantly by reflective cognitive style, β = .13, and less advanced mentalizing, β = .05. Low cultural exposure predicted about 90% higher odds of atheism than did peak cognitive reflection, and cognitive reflection only predicted disbelief among those relatively low in cultural exposure to religion. This highlights the utility of considering both evolved intuitions and transmitted culture and emphasizes the dual roles of content- and context-biased social learning in the cultural transmission of disbelief (preprint https://psyarxiv.com/e29rt/ ).

scholarly journals Neural Collaborative For Music Recommendation System

2021 ◽  
Vol 1071 (1) ◽  
pp. 012021
Author(s):  
Abba Suganda Girsang ◽  
Antoni Wibowo ◽  
Jason ◽  
Roslynlia
Keyword(s):  
Recommendation System ◽  
Music Recommendation ◽  
Music Recommendation System
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