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Volumn , Issue , 2013, Pages 189-194

The million musical tweets dataset: What can we learn from microblogs

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION RETRIEVAL;

EID: 84897638496     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (73)

References (24)
  • 4
    • 64649105397 scopus 로고    scopus 로고
    • Content-based music information retrieval: Current directions and future challenges
    • April
    • Michael A. Casey, Remco Veltkamp, Masataka Goto, Marc Leman, Christophe Rhodes, and Malcolm Slaney. Content-Based Music Information Retrieval: Current Directions and Future Challenges. Proceedings of the IEEE, 96:668–696, April 2008.
    • (2008) Proceedings of the IEEE , vol.96 , pp. 668-696
    • Casey, M.A.1    Veltkamp, R.2    Goto, M.3    Leman, M.4    Rhodes, C.5    Slaney, M.6
  • 9
    • 77950364314 scopus 로고    scopus 로고
    • Collaborative filtering with temporal dynamics
    • April
    • Yehuda Koren. Collaborative filtering with temporal dynamics. Communications of the ACM, 53(4):89, April 2010.
    • (2010) Communications of the ACM , vol.53 , Issue.4 , pp. 89
    • Koren, Y.1
  • 14
    • 85085133306 scopus 로고    scopus 로고
    • You are what you tweet: Analyzing twitter for public health
    • Michael J. Paul and Mark Dredze. You Are What You Tweet: Analyzing Twitter for Public Health. Artificial Intelligence, pages 265–272, 2011.
    • (2011) Artificial Intelligence , pp. 265-272
    • Paul, M.J.1    Dredze, M.2
  • 18
    • 84875426052 scopus 로고    scopus 로고
    • Leveraging microblogs for spatiotemporal music information retrieval
    • Markus Schedl. Leveraging Microblogs for Spatiotemporal Music Information Retrieval. Lecture Notes In Computer Science, 7814:796–799, 2013.
    • (2013) Lecture Notes In Computer Science , vol.7814 , pp. 796-799
    • Schedl, M.1
  • 20
    • 84919420638 scopus 로고    scopus 로고
    • Harvesting microblogs for contextual music similarity estimation - a co-occurrence-based framework
    • Markus Schedl, David Hauger, and Julián Urbano. Harvesting microblogs for contextual music similarity estimation - a co-occurrence-based framework. Multimedia Systems, 2013.
    • (2013) Multimedia Systems
    • Schedl, M.1    Hauger, D.2    Urbano, J.3
  • 22
    • 85069817928 scopus 로고    scopus 로고
    • PhD thesis, Florida International University, Miami, FL, USA, AAI3472062
    • Bo Shao. User-centric music information retrieval. PhD thesis, Florida International University, Miami, FL, USA, 2011. AAI3472062.
    • (2011) User-Centric Music Information Retrieval
    • Shao, B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.