On the Importance of Considering Country-specific Aspects on the Online-Market: An Example of Music Recommendation Considering Country-Specific Mainstream
暂无分享,去创建一个
[1] Christine Bauer,et al. A consolidated view of context for intelligent systems , 2017, J. Ambient Intell. Smart Environ..
[2] Daniel G. Brown,et al. On Cultural, Textual and Experiential Aspects of Music Mood , 2014, ISMIR.
[3] David Bawden,et al. The dark side of information: overload, anxiety and other paradoxes and pathologies , 2009, J. Inf. Sci..
[4] S. Gosling,et al. PERSONALITY PROCESSES AND INDIVIDUAL DIFFERENCES The Do Re Mi’s of Everyday Life: The Structure and Personality Correlates of Music Preferences , 2003 .
[5] David S. Rosenblum,et al. Context-aware mobile music recommendation for daily activities , 2012, ACM Multimedia.
[6] M. Delsing,et al. Intergenerational Continuity of Taste: Parental and Adolescent Music Preferences , 2011 .
[7] Ann Colley,et al. Young People's Musical Taste: Relationship With Gender and Gender‐Related Traits1 , 2008 .
[8] Chris Anderson,et al. The Long Tail: Why the Future of Business is Selling Less of More , 2006 .
[9] Michael R. Lyu,et al. Improving Recommender Systems by Incorporating Social Contextual Information , 2011, TOIS.
[10] Michael A. Casey. Content-Based Music Information Retrieval , 2008 .
[11] Markus Schedl,et al. The LFM-1b Dataset for Music Retrieval and Recommendation , 2016, ICMR.
[12] Òscar Celma,et al. Music Recommendation and Discovery - The Long Tail, Long Fail, and Long Play in the Digital Music Space , 2010 .
[13] Toby Bennett. The Production and Consumption of Music in the Digital Age , 2017 .
[14] Terence Magno,et al. A Comparison of Signal Based Music Recommendation to Genre Labels, Collaborative Filtering, Musicological Analysis, Human Recommendation and Random Baseline , 2008, ISMIR.
[15] Yuan-Chun Jiang,et al. Diversified Recommendation Incorporating Item Content Information Based on MOEA/D , 2016, 2016 49th Hawaii International Conference on System Sciences (HICSS).
[16] J. Avery,et al. The long tail. , 1995, Journal of the Tennessee Medical Association.
[17] Zhenyu Wang,et al. A Music Recommendation Algorithm Based on Hybrid Collaborative Filtering Technique , 2015, SMP.
[18] Mark Sandler,et al. Learning Latent Semantic Models for Music from Social Tags , 2008 .
[19] Peter Knees,et al. Exploring the music similarity space on the web , 2011, TOIS.
[20] Xiao Hu,et al. Cross-cultural similarities and differences in music mood perception , 2014 .
[21] Tao Mei,et al. Just-for-Me: An Adaptive Personalization System for Location-Aware Social Music Recommendation , 2014, ICMR.
[22] Gregory D. Abowd,et al. Towards a Better Understanding of Context and Context-Awareness , 1999, HUC.
[23] Pedro Cano,et al. From hits to niches?: or how popular artists can bias music recommendation and discovery , 2008, NETFLIX '08.
[24] Dmitry Bogdanov,et al. How Much Metadata Do We Need in Music Recommendation? A Subjective Evaluation Using Preference Sets , 2011, ISMIR.
[25] Markus Schedl,et al. Tailoring Music Recommendations to Users by Considering Diversity, Mainstreaminess, and Novelty , 2015, SIGIR.
[26] Audrey Laplante,et al. Improving Music Recommender Systems: What Can We Learn from Research on Music Tastes? , 2014, ISMIR.
[27] Yehuda Koren,et al. Advances in Collaborative Filtering , 2011, Recommender Systems Handbook.
[28] Katayoun Farrahi,et al. On the Influence of User Characteristics on Music Recommendation Algorithms , 2015, ECIR.
[29] R. Brown,et al. Music preferences and personality among Japanese university students. , 2012, International journal of psychology : Journal international de psychologie.
[30] Oliver Budzinski,et al. Do preferences for pop music converge across countries? – Empirical evidence from the Eurovision Song Contest , 2017 .
[31] Paul Rutten,et al. Local popular music on the national and international markets , 1991 .
[32] Paul Lamere,et al. Generating transparent, steerable recommendations from textual descriptions of items , 2009, RecSys '09.
[33] Christine Bauer,et al. Distance- and Rank-based Music Mainstreaminess Measurement , 2017, UMAP.
[34] Hyung Jun Ahn,et al. Utilizing Popularity Characteristics for Product Recommendation , 2006, Int. J. Electron. Commer..
[35] Emilia Gómez,et al. Semantic audio content-based music recommendation and visualization based on user preference examples , 2013, Inf. Process. Manag..
[36] Josep Lluís de la Rosa i Esteva,et al. A Taxonomy of Recommender Agents on the Internet , 2003, Artificial Intelligence Review.
[37] Gediminas Adomavicius,et al. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.
[38] R. Armstrong. The Long Tail: Why the Future of Business Is Selling Less of More , 2008 .
[39] Arun Sundararajan,et al. Recommendation Networks and the Long Tail of Electronic Commerce , 2010, MIS Q..
[40] Markus Schedl,et al. Ameliorating Music Recommendation: Integrating Music Content, Music Context, and User Context for Improved Music Retrieval and Recommendation , 2013, MoMM '13.
[41] Peter Knees,et al. Music Recommender Systems , 2015, Recommender Systems Handbook.
[42] José I. Rojas-Méndez,et al. Identity, culture, dispositions and behavior: A cross-national examination of globalization and culture change , 2016 .
[43] Catherine J. Stevens,et al. Music Perception and Cognition: A Review of Recent Cross-Cultural Research , 2012, Top. Cogn. Sci..
[44] Christine Bauer,et al. Music Recommender Systems Challenges and Opportunities for Non-Superstar Artists , 2017, Bled eConference.
[45] Markus Schedl,et al. Music Information Retrieval: Recent Developments and Applications , 2014, Found. Trends Inf. Retr..
[46] Gert R. G. Lanckriet,et al. Combining audio content and social context for semantic music discovery , 2009, SIGIR.
[47] Greg Linden,et al. Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .
[48] JungAe Yang,et al. Effects of Popularity-Based News Recommendations (“Most-Viewed”) on Users' Exposure to Online News , 2016 .
[49] Ronald Fischer,et al. How Shared Preferences in Music Create Bonds Between People , 2011, Personality & social psychology bulletin.
[50] Ruslan Salakhutdinov,et al. Probabilistic Matrix Factorization , 2007, NIPS.
[51] Peter Knees,et al. Prediction of User Demographics from Music Listening Habits , 2017, CBMI.
[52] B. McSweeney. Hofstede’s Model of National Cultural Differences and their Consequences: A Triumph of Faith - a Failure of Analysis , 2002 .
[53] M. L. Jones. Hofstede - Culturally questionable? , 2007 .
[54] Marc Leman,et al. Content-Based Music Information Retrieval: Current Directions and Future Challenges , 2008, Proceedings of the IEEE.
[55] Man K. Xu,et al. Music through the ages: Trends in musical engagement and preferences from adolescence through middle adulthood. , 2013, Journal of personality and social psychology.
[56] Thomas Hess,et al. The Value of a Recommendation: The Role of Social Ties in Social Recommender Systems , 2014, 2014 47th Hawaii International Conference on System Sciences.
[57] Young Min Baek,et al. Relationship Between Cultural Distance and Cross-Cultural Music Video Consumption on YouTube , 2015 .
[58] Malcolm Slaney,et al. Web-Scale Multimedia Analysis: Does Content Matter? , 2011, IEEE MultiMedia.
[59] Elena Karahanna,et al. Peer-Based Recommendations in Online B2C E-Commerce: Comparing Collaborative Personalization and Social Network-Based Personalization , 2012, 2012 45th Hawaii International Conference on System Sciences.
[60] Gediminas Adomavicius,et al. Context-aware recommender systems , 2008, RecSys '08.
[61] Ichiro Fujinaga,et al. Automatic Music Recommendation Systems: Do Demographic, Profiling, and Contextual Features Improve Their Performance? , 2016, ISMIR.