A graph-based method for playlist generation

Debora Correa, Alexandre L. M Levada, Luciano da F Costa

Research output: Chapter in Book/Conference paperConference paperpeer-review


The advance of online music libraries has increased the importance
of recommendation systems. The task of automatic playlist
generation naturally arises as an interesting approach to this problem.
Most of existing applications use some similarity criterion between the
songs or are based on manual user interaction. In this work, we propose
a novel algorithm for automatic playlist generation based on paths
in Minimum Spanning Trees (MST’s) of music networks. A motivation
is to incorporate the relationship between music genres and expression
of emotions by capturing the presence of temporal rhythmic patterns.
One of the major advantages of the proposed method is the use of edge
weights in the searching process (maximizing the similarity between subsequent
songs), while Breadth-First (BF) and Depth-First (DF) search
algorithms assume the hypothesis that all the songs are equidistant.
Original languageEnglish
Title of host publicationProceedings of the 9th International Symposium on Computer Music Modelling and Retrieval
EditorsMathieu Barthet, Simon Dixon
Place of PublicationEngland
PublisherComputer Music Modeling and Retrieval
Publication statusPublished - 2012
Externally publishedYes
Event 9th International Symposium on Computer Music Modelling and Retrieval: CMMR - London, United Kingdom
Duration: 19 Jun 201222 Jun 2012


Conference 9th International Symposium on Computer Music Modelling and Retrieval
Country/TerritoryUnited Kingdom


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