Nested Contexts of Music Information Retrieval: A Framework of Contextual Factors

被引:1
|
作者
Yang, Yuyu [1 ]
Capra, Rob [1 ]
机构
[1] Univ North Carolina, Chapel Hill, NC 27515 USA
关键词
D O I
10.1145/3576840.3578322
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Music listening is heavily influenced by contexts, and contextual factors can shape users' interaction with music information retrieval (MIR) systems. To better design context-sensitive user experiences in MIR systems, in this paper, we present a review of prior studies on how contexts are associated with user behavior in MIR systems. Contextual factors considered include interaction design, age, personality, time of day, activity, motivation, nationality, etc. Based on the review, we introduce a framework to consider these contextual factors in a consistent and organized way. The framework is adapted from Ingwersen and Jarvelin's 2006 nested contexts framework, and has four layers: 1) MIR/system contexts that focus on MIR systems themselves, including both hardware and software; 2) situational contexts that describe varied and transient daily situations where users interact with MIR systems; 3) personal contexts that focus on the more stable personal characteristics; and 4) social and cultural contexts that describe the characteristics of users' environments. We also present an example to illustrate how to systematically analyze user contexts by using the framework. Finally, we discuss several areas for possible future studies.
引用
收藏
页码:368 / 372
页数:5
相关论文
共 50 条
  • [21] Editorial—Music Information Retrieval
    Alicja A. Wieczorkowska
    Zbigniew W. Ras
    Journal of Intelligent Information Systems, 2003, 21 : 5 - 8
  • [22] Music information retrieval systems
    Birmingham, W
    Meek, C
    O'Malley, K
    Pardo, B
    Shifrin, J
    DR DOBBS JOURNAL, 2003, 28 (09): : 50 - 53
  • [23] Evaluation in Music Information Retrieval
    Julián Urbano
    Markus Schedl
    Xavier Serra
    Journal of Intelligent Information Systems, 2013, 41 : 345 - 369
  • [24] Informetrics and music information retrieval
    Downie, JS
    CANADIAN JOURNAL OF INFORMATION AND LIBRARY SCIENCE-REVUE CANADIENNE DES SCIENCES DE L INFORMATION ET DE BIBLIOTHECONOMIE, 1998, 23 (1-2): : 88 - 88
  • [25] Music information retrieval on the internet
    Mazur Z.
    Wiklak K.
    Advances in Intelligent and Soft Computing, 2010, 80 : 229 - 243
  • [26] Hooked on Music Information Retrieval
    De Haas, W. Bas
    Wiering, Frans
    EMPIRICAL MUSICOLOGY REVIEW, 2010, 5 (04): : 176 - 185
  • [27] Evaluation in Music Information Retrieval
    Urbano, Julian
    Schedl, Markus
    Serra, Xavier
    JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, 2013, 41 (03) : 345 - 369
  • [28] A system for Music Information Retrieval
    Lahart, O
    O'Riordan, C
    ARTIFICIAL INTELLIGENCE AND COGNITIVE SCIENCE, PROCEEDINGS, 2002, 2464 : 197 - 202
  • [29] A Framework for Pattern based Melody Matching for Content based Music Information Retrieval
    Vikram, D.
    Shashi, M.
    PROCEEDINGS OF THE 2017 INTELLIGENT SYSTEMS CONFERENCE (INTELLISYS), 2017, : 470 - 475
  • [30] Toward a universal, meta-theoretical framework for music information classification and retrieval
    Weissenberger, Lynnsey
    JOURNAL OF DOCUMENTATION, 2015, 71 (05) : 917 - 937