HORST 17.09.2009

yet another SocialFacebookiPhoneAndroidTwitterHotMusicSharingStreamingApp ???

HORST 17.09.2009

Nein.

HOlistic Recommender & Storytelling Technology

HORST 17.09.2009

HORST = 1 Option

?

HORST 17.09.2009

Die sogenannten User sind ja auch Menschen. Vielfalt, Emotion.

HORST 17.09.2009

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TYPMusiker, Musikpoweruser, Konzertgänger, CD-KäuferComputerforscher (DFKI), Recommender Vorlesung (Pop Akademie), Social Media Projektleiter (DFKI Berlin),Gründer

MUSIC INTERESTElectronica, Funk, Soul, Hamburger Schule, Indietronics, Glitch, Minimal, Jazz, NuTango

MOODContext-related: Concentrated <> Ecstatic

HORST 17.09.2009

HORST 17.09.2009

Technologie ist toll. Manchmal ein wenig kühl. Vielfalt, Präzision.

HORST 17.09.2009

Empfehlungsmaschinen funktionieren prinzipiell ...3 klassische Ansätze: - Collaborative Filtering (CF)- Content-Based Filtering (CBF)- Hybrid: Kombinationen von CF+CBFNeuere Ansätze- Social: Blip,Hypemachine,TwitterDJ,Mashups- Semantic: DBTune

HORST 17.09.2009

Collaborative Filtering:Implizit/Explizit per User

Stephan Martin Dominik!

Song Nr.1 60mal / Tag - 99mal / 2005!

Song Nr.2 3 mal / Woche 4mal / 2005 -!

Song Nr.3 1 mal / 2006 20mal / Woche -!

HORST 17.09.2009

Content-based Filtering: Manuelle Erfassung

Tonart Taktart Geschlecht!

Song Nr.1 D Moll 4/4 weiblich!

Song Nr.2 D Dur 3/4 männlich!

Song Nr.3 A Dur 4/4 -!

HORST 17.09.2009

Content-based Filtering: Maschinelle Erfassung

Klangverlauf WWW-Infos Liedtext!

Song Nr.1 funky, Duo „..so lovely..“!

Song Nr.2 traditionell „ .. my Love“!

Song Nr.3 instrumental „“!

HORST 17.09.2009

Social: Blogs, Microblogs, Mashups, ...

HORST 17.09.2009

Social: Blogs, Microblogs, Mashups, ...

HORST 17.09.2009

Social: Blogs, Microblogs, Mashups(G.Jost), ...

!"#$%%$&'()*&++,,,-./.$01234%#%%-5/.+6778+76+%29:.;(4*$;.25(<0$;=%<*>.;

=$91;.#9<5;9$3?<5$+@'

HORST 17.09.2009

Social: Blogs, Microblogs, Mashups(J.Herkowitz), ...

!"#$%%$&'()&**+++,-%./0%%1234,4.5*6778*79*%0:$2:;$<)$=15$>:;/%1)?5;

=$4.55$>@$=,':5%AB

HORST 17.09.2009

Empfehlungsmaschinen funktionieren ... gut genug?[MagnoSable ISMIR2008] A Comparison of Signal-based Music Recommendation to Genre Labels, Collaborative Filtering, Musicological Analysis, Human Recommendation, and Random Baseline

!!! 15 Probanden !!! YES

HORST 17.09.2009

Empfehlungsmaschinen funktionieren ... gut genug?[PachetRoy ISMIR2008] Hit Song Science is not yet a Science

!!! 32.000 Songs, HIFIND Experten Daten!!! NO

HORST 17.09.2009

Empfehlungsmaschinen funktionieren ... gut genug?[GodfreyChordia ISMIR2008] Hubs and Homogenity: Improving Content-Based Music Modeling

!!! 617 Songs, OpenNap Experten Daten!!! ?

HORST 17.09.2009

Empfehlungsmaschinen funktionieren ... gut genug?[Salganik et al SCIENCE2006] Experimental Study of Inequality and Unpredictability in an Artifical Cultural Market

!!! 14341 Probanden !!! NO

HORST 17.09.2009

Empfehlungsmaschinen funktionieren ... gut genug?[FlederHosanagar ManagementScience2009] Blockbuster Culture‘s Next Rise or Fall: The Impact of Recommender Systems on Sales Diversity

!!! Mathemat.Simulation !!! ?

HORST 17.09.2009

Empfehlungsmaschinen funktionieren ... gut genug?[BergerLeMens PNAS2009] How Adoption Speed affects the Abandonment of Cultural Tastes

!!! Verwendung statistischer externer Daten !!!„adopt

quickly=die fast“

HORST 17.09.2009

Empfehlungsmaschinen funktionieren ... gut genug?

CF even better than HYBRID

[Celma PH.D THESIS2009] Music Recommendation and Discovery in the Long Tail

!!! 288 Probanden !!! !!! 3 verschiedene Empfehlungssysteme!!!

HORST 17.09.2009

Semantik und Storytelling, was soll das jetzt?

HORST 17.09.2009

Musikalische Fakten sind digital verfügbar

Was ist damit möglich? Konzepte

AIR

PHOENIX

CASSIUS

Philippe Zdar

Etienne de Crecy

Thomas Mars

Sofia CoppolaBeth Hirsch

Gwen McRae

Pharell Williams

HORST 17.09.2009

Angel

Miner‘s SonAlltogether

All this love that I‘m giving

ORANGE

Virgin Suicides

Lost in Translation

Eyewater

Feeling for you

Too Young

J.B. Dunkel

Rhodes

Was ist damit möglich? Beziehungen

HORST 17.09.2009

composed

composed

played

containsdirected

directed

contains soundtrackcomposed

married

lead singermember

friends

member

member

tour manager

relatedcomposed

composed

performed

performed

contains a sample

friends

worked with

2006 charts 65

Was ist damit möglich? Jeder Pfad eine Story!

HORST 17.09.2009

composed

composed

played

contains directed

directed

contains soundtrackcomposed

married

lead singermemberfriends

member

member

tour manager

relatedcomposed

composed

performed

performedcontains a sample

friendsAIR

PHOENIX

CASSIUS

Philippe Zdar

Etienne de Crecy

Thomas Mars

Sofia CoppolaBeth Hirsch

Gwen McRae

Pharell Williams Angel

Miner‘s SonAlltogether

All this love that I‘m giving

ORANGE

Eyewater

Feeling for you

Too Young

J.B. Dunkel

Rhodes

Virgin Suicides

Lost in Translation

worked with

2006 charts 65

Jeder Pfad eine Story! Persönliche Aspekte

HORST 17.09.2009

composed

composed

played

contains directed

directed

contains soundtrackcomposed

married

lead singermemberfriends

member

member

tour manager

relatedcomposed

composed

performed

2006 charts 65

performedcontains a sample

friendsAIR

PHOENIX

CASSIUS

Philippe Zdar

Etienne de Crecy

Thomas Mars

Sofia CoppolaBeth Hirsch

Gwen McRae

Pharell Williams Angel

Miner‘s SonAlltogether

All this love that I‘m giving

ORANGE

Eyewater

Feeling for you

Too Young

J.B. Dunkel

Rhodes

Virgin Suicides

Lost in Translation

worked with

HORST 17.09.2009

Interessante Stories von Maschinen? ja, das ist hart, ergo forschungsrelevant

HORST 17.09.2009

„Fresh Brainfood“ Algorithm Design[Wilcock 200x] Talking OWLs: Towards an Ontology Verbalizer[Galanis et al 2009] An Open-Source Natural Language Generator for OWL Ontologies and its Use in Protégé and Second Life[Górka et al 2007] Information System Based on Natural Language Generation from Ontology

HORST 17.09.2009

Budget?Sie machen wohl Witze. 100% VC-free, kein direktes Research Funding

HORST 17.09.2009

GRAFIX

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Co-Work: Co-Create, Co-Design, Co-Research, Co-XVisual & Brand Design: 2erPackResearch & Experience Design: DFKI,...CBF+CF-Product Support: BMAT(?),DFKI-Openeer,...Social Media Monitoring: tiqqer(?),...MusicBiz Feedback: Sony,Aupeo,MotorFM,Musicload SocioCulturalMusicManagement Input+Students: Pop Akademie SMIXLab, Universität Potsdam,...

HORST 17.09.2009

... und die sogenannten User abholen ... Vielfalt, Emotion!

HORST 17.09.2009

... wenigstens viral? Identifikationspotenzial scheint vorhanden

lovehorst.com