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Word Occurrence Based Extraction of Work Contributors from Statements of Responsibility

机译:从责任陈述的工作贡献者的挑选

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This paper addresses the identification of all contributors of an intellectual work, when they are recorded in bibliographic data but in unstructured form. National bibliographies are very reliable on representing the first author of a work, but frequently, secondary contributors are represented in the statements of responsibility that are transcribed by the cataloguer from the book into the bibliographic records. The identification of work contributors mentioned in statements of responsibility is a typical motivation for the application of information extraction techniques. This paper presents an approach developed for the specific application scenario of the ARROW rights infrastructure being deployed in several European countries to assist in the determination of the copyright status of works that may not be under public domain. Our approach performed reliably in most languages and bibliographic datasets of at least one million records, achieving precision and recall above 0.97 on five of the six evaluated datasets. We conclude that the approach can be reliably applied to other national bibliographies and languages.
机译:本文满足了识别知识产权的所有贡献者,当他们在书目数据中记录但非结构化形式。国家书目是非常可靠的,代表一项工作的第一作者,但经常,中等贡献者在责任的陈述中代表,该责任由Cataloguer从书中转录到书目记录中。责任陈述中提到的工作贡献者的识别是应用信息提取技术的典型动机。本文介绍了一种为箭头权基础设施的特定应用方案开发的方法,该方法部署在几个欧洲各国,协助确定可能不在公共领域的作品的版权状况。我们的方法在大多数语言和书目数据集中可靠地进行至少一百万条记录,在六个评估数据集中五个实现精度并召回0.97以上。我们得出结论,该方法可以可靠地应用于其他国家书目和语言。

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