About Contact Help us

Join us ! Publish !

Interaction Design Foundation

Free educational materials - made by the world's technology elite

About sponsorships

References

Jin Ha Lee

iPad and tablet version

Publication statistics

Pub. period:2007-2012
Pub. count:6
Number of co-authors:7

Co-authors

Number of publications with 3 favourite co-authors:

M. Cameron Jones:3
J. Stephen Downie:2
Anatoliy A. Gruzd:2

Productive colleagues

Jin Ha Lee's 3 most productive colleagues in number of publications:

J. Stephen Downie:18
M. Cameron Jones:9
Xiao Hu:9

Calendar

May 27

13th Intl. Conf. on New Interfaces for Musical Expression

May 28

Graphics Interface 2013

May 29

Boston UXPA Usability and UX Conf. 2013

May 24

“ For a list of all the ways technology has failed to improve the quality of life, please press three. ”

-- Alice Kahn

Share this quote on...
Get more quotes via RSS or by joining our Usability Quote of the Day Facebook Page

Featured chapter

Read the fascinating history of Wearable Computing, told by its father, Steve Mann

Read Steve's chapter !

Help us help you!

Spread the word:
Donate
Other ways to help

Jin Ha Lee

Add description

← Button will not work: You have not enabled Javascript. How do I enable it?

Rename / change spelling

Add publication

← Button will not work: You have not enabled Javascript. How do I enable it?

Publications by Jin Ha Lee (bibliography)

2012

Edit | Del

Lee, Jin Ha and Hu, Xiao (2012): Generating ground truth for music mood classification using mechanical turk. In: JCDL12 Proceedings of the 2012 Joint International Conference on Digital Libraries 2012. pp. 129-138.

“Mood is an important access point in music digital libraries and online music repositories, but generating ground truth for evaluating various music mood classification algorithms is a challenging problem. This is because collecting enough human judgments is time-consuming and costly due to the subjectivity of music mood. In this study, we explore the viability of crowdsourcing music mood classification judgments using Amazon Mechanical Turk (MTurk). Specifically, we compare the mood classification judgments collected for the annual Music Information Retrieval Evaluation eXchange (MIREX) with judgments collected using MTurk. Our data show that the overall distribution of mood clusters and agreement rates from MIREX and MTurk were comparable. However, Turkers tended to agree less with the pre-labeled mood clusters than MIREX evaluators. The system evaluation results generated using both sets of data were mostly the same except for detecting one statistically significant pair using Friedman's test. We conclude that MTurk can potentially serve as a viable alternative for ground truth collection, with some reservation with regards to particular mood clusters.”

Edit | Del

Lee, Jin Ha, Hill, Trent and Work, Lauren (2012): What does music mood mean for real users?. In: Proceedings of the 2012 iConference 2012. pp. 112-119.

“Mood has recently received increasing attention as an interesting approach for organizing and accessing music. Our understanding of how users determine and describe music mood, however, is not fully developed. In this exploratory study, we investigate the concept of music mood from the end-user's perspective. In particular, we want to see how users describe music mood in their own terms as they react to different musical features. We investigate this by asking users to provide mood tags for various cover versions of the same song. The findings suggest that users rely on a small limited set of mood terms, although they do use a wide variety of terms. Typically, certain moods seem to carry over multiple cover versions despite differences in musical features. Along with lyrics, tempo, instrumentation, and delivery, factors like sources of mood, genre, musical expectancy, cultural context, etc. also seem to affect how people feel about music.”

Edit | Del

Karlova, Natascha and Lee, Jin Ha (2012): Playing with information: information work in online gaming environments. In: Proceedings of the 2012 iConference 2012. pp. 441-443.

“Digital games are saturated with information. Massively Multiplayer Online games (MMOs) require players to collect, organize, manage, and interpret vast volumes and varieties of information in a distributed, networked environment. Yet, they often provide players insufficient tools to effectively accomplish these information tasks. In response, some members of the player community build modifications (mods) and addons to the game software. Mods and addons usefully and creatively address some problems of utilizing information in digital environments; by analyzing them, we can gain insights into possibilities for organizing information in digital environments.”

2011

Edit | Del

Lee, Jin Ha and Jones, M. Cameron (2011): Thinking inside the XBox: elements of information organization in video games. In: Proceedings of the 2011 iConference 2011. pp. 706-707.

“Video games are a novel and unique context in which numerous principles of information organization can be observed. In this poster, we explore the intersection of video games and formal information organization by examining several examples from popular video games. By doing so, we highlight some of the common organization principles that are applied in video game design, and perhaps discover new ways of organizing information objects and assess their application in real life contexts.”

2007

Edit | Del

Downie, J. Stephen, Lee, Jin Ha, Gruzd, Anatoliy A. and Jones, M. Cameron (2007): Toward an understanding of similarity judgments for music digital library evaluation. In: JCDL07: Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries 2007. pp. 307-308.

“This paper presents an analysis of 7,602 similarity judgments collected for the Symbolic Melodic Similarity (SMS) and Audio Music Similarity and Retrieval (AMS) evaluation tasks in the 2006 Music Information Retrieval Evaluation eXchange (MIREX). We discuss the influence of task definitions, as well as evaluation metrics on user perceptions of music similarity, and provide recommendations for future Music Digital Library/Music Information Retrieval research pertaining to music similarity.”

Edit | Del

Gruzd, Anatoliy A., Downie, J. Stephen, Jones, M. Cameron and Lee, Jin Ha (2007): Evalutron 6000: collecting music relevance judgments. In: JCDL07: Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries 2007. p. 507.

Add publication