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dc.contributor.advisorKhriyenko Oleksiy
dc.contributor.authorRumiantcev, Mikhail
dc.date.accessioned2017-03-07T08:38:40Z
dc.date.available2017-03-07T08:38:40Z
dc.date.issued2017
dc.identifier.otheroai:jykdok.linneanet.fi:1674826
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/53196
dc.description.abstractIn respect of the big amounts of music available in the web, people met the problem of choice. From another side, practically unlimited resources can bring us new opportunities in the music context. Efficient data management engines which are smart and self managed are in demand nowadays in the music industry to handle music sources amounts of which are coming towards to infinity continuously. This study demonstrates feasibility of the emotional based personalization of music recommendation system. There is still gap between human and artificial intelligence, robotics do not have intuition and emotions which represent critical point of recommendations. Taking into account significant influence of music to human emotions, we can notice that it can be a strong chain between human emotions and machines. This work provides the novel implementation of the music recommendation system based on emotional personalization, which manages human emotions by selecting and delivering music tracks based on their previous personal listening experience, collaborative and classification filtering.en
dc.format.extent1 verkkoaineisto (104 sivua)
dc.language.isoeng
dc.rightsJulkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.fi
dc.rightsThis publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.en
dc.subject.otherrecommendation system
dc.subject.othermusic
dc.subject.otherweb services
dc.subject.othermachine learning
dc.titleMusic adviser : emotion-driven music recommendation ecosystem
dc.title.alternativeEmotion-driven music recommendation ecosystem
dc.identifier.urnURN:NBN:fi:jyu-201703071591
dc.type.ontasotPro gradufi
dc.type.ontasotMaster's thesisen
dc.contributor.tiedekuntaInformaatioteknologian tiedekuntafi
dc.contributor.tiedekuntaFaculty of Information Technologyen
dc.contributor.laitosTietotekniikan laitos
dc.contributor.laitosTietotekniikan laitosfi
dc.contributor.laitosDepartment of Mathematical Information Technologyen
dc.contributor.yliopistoUniversity of Jyväskyläen
dc.contributor.yliopistoJyväskylän yliopistofi
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.date.updated2017-03-07T08:38:41Z
dc.rights.accesslevelopenAccessfi
dc.contributor.oppiainekoodi602
dc.subject.ysomusiikki
dc.subject.ysokoneoppiminen
dc.subject.ysosuosittelujärjestelmät
dc.subject.ysoverkkopalvelut


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