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Music discovery on the net

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Music discovery on the net
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  • Added: April, 14th 2011
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  • Pages: 15
  • Tags: auto, analysis, freakomendations, filtering, webservice, recommendation, berlin, bcberlin3, tagging, semantic, content, manipulation, collaborative, technology, music, barcamp3, recommednation
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  • Name: petra

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Music discovery on the net Barcamp3, Berlin Petar Djekic October 18th, 2008 From phonograph to widgets Widget Mobile Web Web PC PC PC Portable Portable Portable Portable TV TV TV TV TV Car Audio Car Audio Car Audio Car Audio Car Audio Radio Radio Radio Radio Radio Radio Phono Phono Phono HiFi system HiFi system HiFi system HiFi system 1890 1920 1930 1950 1980 1990 2000 Source: own, Wikipedia ’08 Yet still.. „iPod classic can „There is are an average of hold up to 30,000 700 songs stored on a U.S. music downloader’s songs“ player.“ „Average MP3 player only 57% full“ Source: Apple 2008, Forrester Research 2008, IPSOS 2006 Music Discovery 4 “The only bad thing about “A wealth of information MySpace is that there creates a poverty of are 100,000 bands and no attention” filtering. I try to find the bands I Herbert A. Simon, Nobel prize might like but often I just winning economist get tired of looking.” 15 year old student, IFPI focus group research, July 2007 Music Discovery 5 Many places, similar technologies Recommendation technologies: Overview  Human behaviour: Recommendations are based on behaviour, e.g., Collaborative filtering using listening or purchase habits  Human annotation: Recommendations are based on annotations and expertise, e.g., ratings, tags, classification into genres, editorial content  Content analysis: Recommendations are based on characteristics of the content itself, e.g., sound density, vocals, tempo, sound color, instruments, volume, dynamics „Freakomendations“: Variety Source: audiobaba „Freakomendations“: Manipulation Source: Paul Lamere, last.fm „Freakomendations“: Cold-start Source: iTunes Genius „Freakomendations“: Relevance Source: mufin.com

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