Reference Hub

This research has been cited in:

Conference
An Innovative Fuzzy Logic-Based Machine Learning Algorithm for Supporting Predictive Analytics on Big Transportation Data2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)10.1109/FUZZ48607.2020.9177823
Conference
Big Data Analytics for Personalized Recommendation Systems2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)10.1109/DASC/PiCom/CBDCom/CyberSciTech.2019.00190
Chapter
Cognitive and Predictive Analytics on Big Open DataCognitive Computing – ICCC 202010.1007/978-3-030-59585-2_8
Conference
Cognitive-Based Hybrid Collaborative Filtering with Rating Scaling on Entropy to Defend Shilling InfluenceProceedings of the 2019 8th International Conference on Networks, Communication and Computing10.1145/3375998.3376040
Chapter
Vertical Data Mining from Relational Data and Its Application to COVID-19 DataBig Data Analyses, Services, and Smart Data10.1007/978-981-15-8731-3_8
Chapter
Big Data Computing and Mining in a Smart WorldBig Data Analyses, Services, and Smart Data10.1007/978-981-15-8731-3_2
Article
Visual Performance of Psychological Factors in Interior Design Under the Background of Artificial IntelligenceFrontiers in Psychology10.3389/fpsyg.2022.941196
Conference
Data. Information and Knowledge Visualization for Frequent Patterns2022 26th International Conference Information Visualisation (IV)10.1109/IV56949.2022.00045
Chapter
Data Science for Big Data Applications and Services: Data Lake Management, Data Analytics and VisualizationBig Data Analyses, Services, and Smart Data10.1007/978-981-15-8731-3_3
Chapter
Big Data Analytics and Mining for Knowledge DiscoveryEncyclopedia of Organizational Knowledge, Administration, and Technology10.4018/978-1-7998-3473-1.ch125
Chapter
Big Data Visualization of Association Rules and Frequent PatternsEncyclopedia of Data Science and Machine Learning10.4018/978-1-7998-9220-5.ch075
Chapter
Big Data Analytics and Mining for Knowledge DiscoveryResearch Anthology on Big Data Analytics, Architectures, and Applications10.4018/978-1-6684-3662-2.ch033
Chapter
Big Data Mining and Analytics With MapReduceEncyclopedia of Data Science and Machine Learning10.4018/978-1-7998-9220-5.ch010

An HSV-Based Visual Analytic System for Data Science on Music and Beyond

Carson K.S. Leung, Yibin Zhang

Source Title: International Journal of Art, Culture, Design, and Technology (IJACDT)8(1)

ISSN: 2155-4196|EISSN: 2155-420X|EISBN13: 9781522567585|DOI: 10.4018/IJACDT.2019010105

Cite Article Cite Article

MLA

Leung, Carson K.S., and Yibin Zhang. "An HSV-Based Visual Analytic System for Data Science on Music and Beyond." IJACDT vol.8, no.1 2019: pp.68-83. http://doi.org/10.4018/IJACDT.2019010105

APA

Leung, C. K. & Zhang, Y. (2019). An HSV-Based Visual Analytic System for Data Science on Music and Beyond. International Journal of Art, Culture, Design, and Technology (IJACDT), 8(1), 68-83. http://doi.org/10.4018/IJACDT.2019010105

Chicago

Leung, Carson K.S., and Yibin Zhang. "An HSV-Based Visual Analytic System for Data Science on Music and Beyond," International Journal of Art, Culture, Design, and Technology (IJACDT) 8, no.1: 68-83. http://doi.org/10.4018/IJACDT.2019010105

Export Reference

Favorite Full-Issue Download

View Full Text HTML

View Full Text PDF

Abstract

In the current era of big data, high volumes of a wide variety of valuable data—which may be of different veracities—can be easily generated or collected at a high speed in various real-life applications related to art, culture, design, engineering, mathematics, science, and technology. A data science solution helps manage, analyze, and mine these big data—such as musical data—for the discovery of interesting information and useful knowledge. As “a picture is worth a thousand words,” a visual representation provided by the data science solution helps visualize the big data and comprehend the mined information and discovered knowledge. This journal article presents a visual analytic system—which uses a hue-saturation-value (HSV) color model to represent big data—for data science on musical data and beyond (e.g., other types of big data).

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.

Username or email: *

Password: *

Forgot individual login password?

Create individual account

An HSV-Based Visual Analytic System for Data Science on Music and Beyond

MLA

APA

Chicago

Export Reference

Abstract

Request Access