Music Data Analysis: A State-of-the-art Survey
Music accounts for a significant chunk of interest among various online activities. This is reflected by wide array of alternatives offered in music related web/mobile apps, information portals, featuring millions of artists, songs and events attracting user activity at similar scale. Availability of large scale structured and unstructured data has attracted similar level of attention by data science community. This paper attempts to offer current state-of-the-art in music related analysis. Various approaches involving machine learning, information theory, social network analysis, semantic web and linked open data are represented in the form of taxonomy along with data sources and use cases addressed by the research community.
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Datasets
Results from the Paper
Ranked #1 on
No-Reference Image Quality Assessment
on 200k Short Texts for Humor Detection
(using extra training data)
| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Uses Extra Training Data |
Benchmark |
|---|---|---|---|---|---|---|---|
| No-Reference Image Quality Assessment | 200k Short Texts for Humor Detection | davido | 14 gestures accuracy | kindness | # 1 |
