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[{"key": "dc.contributor.advisor", "value": "R\u00f6nkk\u00f6, Mikko", "language": null, "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Koskela, Pentti", "language": null, "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2017-07-10T20:36:05Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2017-07-10T20:36:05Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2017", "language": null, "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.other", "value": "oai:jykdok.linneanet.fi:1704875", "language": null, "element": "identifier", "qualifier": "other", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/54905", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "Suuri sis\u00e4lt\u00f6valikoima eri internet palveluissa, kuten verkkokaupoissa, voi aiheuttaa liian suurta informaatiom\u00e4\u00e4r\u00e4\u00e4, mik\u00e4 heikent\u00e4\u00e4 asiakaskokemusta. Suositteluj\u00e4rjestelm\u00e4t ovat teknologioita, jotka tukevat asiakkaan p\u00e4\u00e4t\u00f6ksentekoa tarjoamalla ennustettuja suosituksia. On yleist\u00e4, ett\u00e4 asiakkaalle n\u00e4ytet\u00e4\u00e4n lista tuotteista, joista asiakas voisi pit\u00e4\u00e4, esimerkiksi top-10 lista elokuvista. Perinteisesti n\u00e4m\u00e4 listat ovat tuotettu k\u00e4ytt\u00e4en perinteist\u00e4 arvosanapohjaista menetelm\u00e4\u00e4, miss\u00e4 tuntemattomille tuotteille ennustetaan arvosana ja j\u00e4rjestetty lista muodostetaan arvosanojen perusteella. Sijoitusperusteinen l\u00e4hestyminen laskee k\u00e4ytt\u00e4jien v\u00e4liset samankaltaisuudet ja ennustaa j\u00e4rjestetyn listan ilman v\u00e4livaihetta liittyen arvosanojen laskemiseen.\nErilaisia suositteluj\u00e4rjestelm\u00e4algoritmeja on julkaistu lukuisia eri k\u00e4ytt\u00f6tarkoituksia varten. Yhteis\u00f6llisen suodatuksen kontekstissa sijoitusperusteiset menetelm\u00e4t ovat yleistyneet j\u00e4rjestettyjen listojen tarkkuuden merkityksen kasvaessa. On olemassa useita hybridivariaatioita miss\u00e4 kaksi tai useampi eri suositteluj\u00e4rjestelm\u00e4tyyppi on yhdistetty. N\u00e4iden suorituskyky\u00e4 ei voida verrata t\u00e4ss\u00e4 tutkielmassa k\u00e4ytettyihin algoritmeihin johtuen niiden erilaisesta toteutustavasta.\nT\u00e4m\u00e4 tutkielma vertaa kolmea erilaista sijoitusperusteista yhteis\u00f6llist\u00e4 suositteluj\u00e4rjestelm\u00e4algoritmia kesken\u00e4\u00e4n, ja vertailee tuloksia perinteisen arvosanaperusteisen algoritmin kanssa. Tulokset osoittavat parannuksen ennustustarkkuudessa sijoitusperusteista algoritmia k\u00e4ytett\u00e4ess\u00e4, verrattuna arvosanaperusteiseen algoritmiin. Lis\u00e4ksi, tulokset osoittavat sijoitusperusteisten algoritmien kehityksen parannuksen viime vuosina.\nPois lukien tieteelliset julkaisut, miss\u00e4 valitut algoritmit ovat esitelty, en l\u00f6yt\u00e4nyt tutkielmaa, miss\u00e4 algoritmeja olisi vertailtu kesken\u00e4\u00e4n. Tarkastelin tuloksia k\u00e4ytt\u00e4en kahta eri arviointimenetelm\u00e4\u00e4, joista Mean Average Precision on v\u00e4hemm\u00e4n k\u00e4ytetty t\u00e4m\u00e4nkaltaisissa tutkimuksissa.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "The vast amount of content on internet services, such as e-commerce sites, can cause information overflow, which leads to a bad user experience. Recommender system is technique to support the user\u2019s decision-making by providing predicted suggestions. It is common that user is provided a list of items in user\u2019s preference, e.g. top-10 list of movies. Traditionally, these ranked lists are generated by using rating-based approaches, where ratings are predicted to unknown items which are then calculated to ranked list. Ranking-based approach calculates similarities between users and predicts a ranked list without the middle-step of predicting the ratings first.\nThere is a number of different collaborative filtering (CF) algorithms for different use cases. In a context of CF, ranking-based approaches are becoming more popular as the importance of ranked list accuracy has increased. However, there are several hybrid implementations where two or more different kind of recommender systems are combined, which performance cannot be compared to the algorithms in this thesis due to implementation differences.\nThis thesis will compare three different ranking-based CF algorithms to each other and compare the results with the rating-based CF paradigm. The results will show the prediction accuracy improvement when using ranking-based approaches compared to a rating-based one. In addition, results will also show how much the performance have been improved in ranking-based CF algorithms in the past years.\nExcluding the research papers where the selected algorithms were introduced, I did not find any research publications where the selected algorithms were compared to each other. I evaluated the results using two different evaluation methods, of which Mean Average Precision is less common in this field of study.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted using Plone Publishing form by Pentti Koskela (pensanko) on 2017-07-10 20:36:05.325934. Form: Pro gradu -lomake (https://kirjasto.jyu.fi/julkaisut/julkaisulomakkeet/pro-gradu-lomake). JyX data: [jyx_publishing-allowed (fi) =True]", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by jyx lomake-julkaisija (jyx-julkaisija.group@korppi.jyu.fi) on 2017-07-10T20:36:05Z\nNo. of bitstreams: 2\nURN:NBN:fi:jyu-201707103285.pdf: 931214 bytes, checksum: c7ace3fd3356d2a3c354f53b3492b51e (MD5)\nlicense.html: 4877 bytes, checksum: 1832ae07631bc4b5e3ec0121ceca1ce4 (MD5)", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2017-07-10T20:36:05Z (GMT). No. of bitstreams: 2\nURN:NBN:fi:jyu-201707103285.pdf: 931214 bytes, checksum: c7ace3fd3356d2a3c354f53b3492b51e (MD5)\nlicense.html: 4877 bytes, checksum: 1832ae07631bc4b5e3ec0121ceca1ce4 (MD5)\n Previous issue date: 2017", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "1 verkkoaineisto (51 sivua)", "language": null, "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.language.iso", "value": "eng", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": "en", "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "recommender systems", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "ranking-oriented collaborative filtering", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "rating-oriented collaborative filtering", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "suositteluj\u00e4rjestelm\u00e4t", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "sijoitusperusteinen yhteis\u00f6llinen suodatus", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "arvosanaperusteinen yhteis\u00f6llinen suodatus", "language": null, "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Comparing ranking-based collaborative filtering algorithms to a rating-based alternative in recommender systems context", "language": null, "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-201707103285", "language": null, "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Master's thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Information Technology", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Informaatioteknologian tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Informaatioteknologia", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Information Systems Science", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Tietoj\u00e4rjestelm\u00e4tiede", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.date.updated", "value": "2017-07-10T20:36:06Z", "language": null, "element": "date", "qualifier": "updated", "schema": "dc"}, {"key": "yvv.contractresearch.funding", "value": "0", "language": null, "element": "contractresearch", "qualifier": "funding", "schema": "yvv"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": "fi", "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.subject.oppiainekoodi", "value": "601", "language": null, "element": "subject", "qualifier": "oppiainekoodi", "schema": "dc"}, {"key": "dc.subject.yso", "value": "suositteluj\u00e4rjestelm\u00e4t", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "suodatus", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}]
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