跨域RDF的自包含NoSQL资源
Self-contained NoSQL Resources for Cross-Domain RDF
摘要：
DBpedia、Freebase和YAGO等跨领域知识库已成为关联数据网络中的知识中心。尽管使几个实际的应用在语义网，大规模的，无模式的性质，这样的图往往排除了研究小组广泛采用它们作为评估测试案例的实体解析和基于实例的本体对齐应用。虽然上述三个知识库之间存在着实际联系，但在资源有限的情况下无法加以应用。一个原因是地面实况文件不是自包含的，这意味着研究人员通常必须执行一系列昂贵的连接（通常在MapReduce中）才能获得可用的信息集。在本文中，我们上传几个公开许可的数据资源到公共云，并使用简单的Hadoop集群编译，并使访问，三个跨域自包含的测试用例，涉及DBpedia，Freebase和YAGO的链接实例。自包含是通过一个简单的NoSQL类JSON序列化格式实现的。这些资源的潜在应用，特别是有关测试迁移学习研究假设，也简要介绍。
英文摘要：
Cross-domain knowledge bases such as DBpedia, Freebase and YAGO have emerged as encyclopedic hubs in the Web of Linked Data. Despite enabling several practical applications in the Semantic Web, the large-scale, schema-free nature of such graphs often precludes research groups from employing them widely as evaluation test cases for entity resolution and instance-based ontology alignment applications. Although the ground-truth linkages between the three knowledge bases above are available, they are not amenable to resource-limited applications. One reason is that the ground-truth files are not self-contained, meaning that a researcher must usually perform a series of expensive joins (typically in MapReduce) to obtain usable information sets. In this paper, we upload several publicly licensed data resources to the public cloud and use simple Hadoop clusters to compile, and make accessible, three cross-domain self-contained test cases involving linked instances from DBpedia, Freebase and YAGO. Self-containment is enabled by virtue of a simple NoSQL JSON-like serialization format. Potential applications for these resources, particularly related to testing transfer learning research hypotheses, are also briefly described.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
