FmFinder: Search and filter your favorite songs

Tuan Nhon Dang, Anushka Anand, Leland Wilkinson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations


Choices in music express our taste and personality. Different people have different collections of favorite songs. The explosive growth of digital media makes it easier to access any songs we want. Consequently, finding the songs best fit to our tastes becomes more challenging. Existing solutions record user patterns of listening to music, then make recommendation lists for users. By applying information visualization techniques to this problem, we are able to provide users with a novel way to explore their list of recommendations. Based on that knowledge, users can filter the songs according to their needs and compare the music tastes of different groups of people.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 8th International Symposium, ISVC 2012, Revised Selected Papers
Number of pages11
EditionPART 1
StatePublished - 2012
Event8th International Symposium on Visual Computing, ISVC 2012 - Rethymnon, Crete, Greece
Duration: Jul 16 2012Jul 18 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7431 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference8th International Symposium on Visual Computing, ISVC 2012
CityRethymnon, Crete


Dive into the research topics of 'FmFinder: Search and filter your favorite songs'. Together they form a unique fingerprint.

Cite this