Recommender systems are one of the most successful applications of data mining and
machine-learning technology in practice. Academic research in the field is historically often …

Most of the time when we listen to music on the radio or on our portable devices, the order in
which the tracks are played is governed by so-called playlists. These playlists are basically …

Acoustic-based music recommender systems have received increasing interest in recent
years. Due to the semantic gap between low level acoustic features and high level music …

This chapter gives an introduction to music recommender systems research. We highlight
the distinctive characteristics of music, as compared to other kinds of media. We then …

There are various kinds of social media information, including different types of objects and
relations among these objects, in music social communities such as Last. fm and Pandora …

Social tagging systems have grown in popularity over the Web in the last years on account
of their simplicity to categorize and retrieve content using open-ended tags. The increasing …

Collaborative tagging, ie the process of assigning metadata in the form of keywords to
shared content by many users, has emerged as an important way to provide information …

Music recommendation is receiving increasing attention as the music industry develops
venues to deliver music over the Internet. The goal of music recommendation is to present …

ABSTRACT A new algorithm for automatic generation of playlists with an inherent sequential
order is presented. Based on a start and end song it creates a smooth transition allowing …

Music consumption is biased towards a few popular artists. For instance, in 2007 only 1% of
all digital tracks accounted for 80% of all sales. Similarly, 1,000 albums accounted for 50 …