Modeling the Complexity of Music Metadata in Semantic Graphs for Exploration and Discovery

Pasquale Lisena, Raphael Troncy, Konstantin Todorov, Manel Achichi
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引用次数: 9

Abstract

Representing and retrieving fine-grained information related to something as complex as music composition, recording and performance is a challenging activity. This complexity requires that the data model enables to describe different outcomes of the creative process, from the writing of the score, to its performance and publishing. In this paper, we show how we design the DOREMUS ontology as an extension of the FRBRoo model in order to represent music metadata coming from different libraries and cultural institutions and how we publish this data as RDF graphs. We designed and re-used several controlled vocabularies that provide common identifiers that overcome the differences in language and alternative forms of needed concepts. These graphs are interlinked to each other and to external resources on the Web of Data. We show how these graphs can be walked through for designing a web-based application providing an exploratory search engine for presenting complex music metadata to the end-user. Finally, we demonstrate how this model and this exploratory application is suitable for answering non-trivial questions collected from experts and is a first step towards a fully fledged recommendation engine.
基于语义图的音乐元数据复杂性建模研究
表示和检索与音乐创作、录音和表演等复杂事物相关的细粒度信息是一项具有挑战性的活动。这种复杂性要求数据模型能够描述创作过程的不同结果,从编写乐谱到演奏和发布。在本文中,我们展示了如何将DOREMUS本体设计为FRBRoo模型的扩展,以表示来自不同图书馆和文化机构的音乐元数据,以及如何将这些数据发布为RDF图。我们设计并重用了几个受控词汇表,这些词汇表提供了公共标识符,克服了语言差异和所需概念的替代形式。这些图表相互连接,并与数据网上的外部资源相连。我们将展示如何通过这些图来设计一个基于web的应用程序,该应用程序提供一个探索性搜索引擎,用于向最终用户呈现复杂的音乐元数据。最后,我们演示了这个模型和这个探索性应用程序如何适合于回答从专家那里收集的重要问题,这是迈向成熟推荐引擎的第一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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