Context-based services have attracted increasing attention because of the prevalence of
sensor-rich mobile devices such as smartphones. The idea is to recommend information that …

Prior user studies in the music information retrieval field have identified different personas
representing the needs, goals, and characteristics of specific user groups for a usercentered …

Music categorization based on acoustic features extracted from music clips and user-defined
tags forms the basis of recent music recommendation applications, because relevant tags …

This paper proposes FocusMusicRecommender, an automated system recommending
background music to listen to while working. Recommendation systems matching user …

This paper aims at leveraging microblogs to address two challenges in music information
retrieval (MIR), similarity estimation between music artists and inferring typical listening …

Incorporating user characteristics and contextual information has shown to be essential
when it comes to personalized music retrieval and recommendation. To this end, the current …

Context-aware recommendation has attracted significant attentions over online sites due to
its smart context adaption in improving recommendation quality. However, the user's instant …

Computational aesthetic evaluation has made remarkable contribution to visual art works,
but its application to music is still rare. Currently, subjective evaluation is still the most …

These days, there are huge amount of multimedia contents that are available for users.
Selecting and exploiting favorite contents from such online available collections is a big …

Context-aware recommender systems (CARS) have been developed to adapt to users'
preferences in different contextual situations. Users' emotions have been demonstrated as …