000028988 001__ 28988
000028988 005__ 20130422152610.0
000028988 0247_ $$2urn$$aurn:nbn:ch:rero-006-110767
000028988 0248_ $$aoai:doc.rero.ch:20120416100806-MJ$$pthesis$$prero_explore$$punisi$$pthesis_urn$$zcdu34$$zreport$$zcdu004$$zbook$$zjournal$$zcdu16$$zpostprint$$zpreprint$$zcdu1$$zdissertation
000028988 041__ $$aeng
000028988 080__ $$a004
000028988 100__ $$aMesnage, Cédric S.$$d1980-04-07
000028988 245__ $$9eng$$aSocial shuffle$$bmusic discovery with tag navigation and social diffusion
000028988 300__ $$a92 p
000028988 502__ $$92011-05-18$$aThèse de doctorat : Università della Svizzera italiana, 2011 ; 2011INFO009
000028988 506__ $$ffree
000028988 520__ $$9eng$$aThis thesis tackles the problem of discovering music for users in a social network, introducing the concept of social shuffle and  its implementation as a live experiment in social based recommendation, Starnet, and show that recommendations based on a  user’s social network is strongly effective in introducing a user to new music that she enjoys. I investigate the generation of tag  clouds using Bayesian models and test the hypothesis that social network information is better than overall popularity for ranking  new and relevant information. I propose three tag cloud generation models based on popularity, topics and social structure. I  conducted two user evaluations to compare the models for search and recommendation of music with social network data  gathered from Last.fm. Our survey shows that search with tag clouds is not practical whereas recommendation is promising. I  report statistical results and compare the performance of the models in generating tag clouds that lead users to discover songs  that they liked and were new to them. I find statistically significant evidence at 5% confidence level that the topic and social  models outperform the popular model. I report on an experiment on social diffusion for music discovery. I describe the  experimental methodology which includes the making of a music videos dataset and the creation of a social application. I give a  statistical analysis of the participants ratings which shows that social diffusion leads to more good recommendations. I conclude  and show that the social shuffle is an effective mechanism for information recommendation and that social relationships are  relevant data to enhance information navigation.
000028988 695__ $$9eng$$aMusic discovery ; Computer science ; Social media and web engineering ; Tag navigation
000028988 700__ $$aJazayeri, Mehdi$$eDir.
000028988 8564_ $$f2011INFO009.pdf$$qapplication/pdf$$s2279963$$uhttp://doc.rero.ch/record/28988/files/2011INFO009.pdf$$yorder:1$$zTexte intégral
000028988 918__ $$aFacoltà di scienze informatiche$$bVia Lambertenghi 10A, CH-6904 Lugano
000028988 919__ $$aUniversità della Svizzera italiana$$bLugano$$ddoc.support@rero.ch
000028988 980__ $$aTHESIS$$bUNISI$$fTH_PHD
000028988 990__ $$a20120416100806-MJ