This paper describes a method for improved access to publisher references in linked data RDF editors using data mining techniques and a large set of library metadata encoded in the MARC21 standard. The corpus is comprised of clustered sets of publishers and publisher locations from the library MARC21 records found in the POD Data Lake, an Ivy+ Library Consortium metadata sharing initiative. The POD Data Lake contains seventy million MARC21 records, forty million of which are unique. The discovery of publisher entity sets described forms the basis for the streamlined description of BIBFRAME Instance entities. This study resulted in two major outputs: 1) A prediction database and 2) sets of publisher location and name association rules. The association rules are the basis of a prototype autosuggestion feature of BIBFRAME Instance entity description properties designed specifically to support the autopopulation of publisher entities in linked data RDF editors.

中文翻译：

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书目实体描述中的出版商参考

本文描述了一种使用数据挖掘技术和以 MARC21 标准编码的大量图书馆元数据改进链接数据 RDF 编辑器中对出版商参考的访问的方法。该语料库由来自 POD 数据湖中的图书馆 MARC21 记录的出版商和出版商位置的集群集组成，POD 数据湖是一项常春藤+图书馆联盟元数据共享计划。POD 数据湖包含 7000 万条 MARC21 记录，其中 4000 万条是唯一的。所描述的发布者实体集的发现构成了 BIBFRAME 实例实体简化描述的基础。这项研究产生了两个主要输出：1) 预测数据库和 2) 发布者位置和名称关联规则集。