MusicWeb: Music Discovery with Open Linked Semantic Metadata

被引:5
作者
Mora-Mcginity, Mariano [1 ]
Allik, Alo [1 ]
Fazekas, Gyorgy [1 ]
Sandler, Mark [1 ]
机构
[1] Queen Mary Univ, London, England
来源
METADATA AND SEMANTICS RESEARCH, MTSR 2016 | 2016年 / 672卷
基金
英国工程与自然科学研究理事会;
关键词
Semantic Web; Linked open data; Music metadata; Semantic audio analysis; Music information retrieval;
D O I
10.1007/978-3-319-49157-8_25
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents MusicWeb, a novel platform for music discovery by linking music artists within a web-based application. MusicWeb provides a browsing experience using connections that are either extra-musical or tangential to music, such as the artists' political affiliation or social influence, or intra-musical, such as the artists' main instrument or most favoured musical key. The platform integrates open linked semantic metadata from various Semantic Web, music recommendation and social media data sources. Artists are linked by various commonalities such as style, geographical location, instrumentation, record label as well as more obscure categories, for instance, artists who have received the same award, have shared the same fate, or belonged to the same organisation. These connections are further enhanced by thematic analysis of journal articles, blog posts and content-based similarity measures focussing on high level musical categories.
引用
收藏
页码:291 / 296
页数:6
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