发表机构
Hasso Plattner Institute; Facultad de Ingeniería（哈索·普拉特纳研究所; 工程学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
WiDiff从Wikidata完整编辑历史中提取变更，提供统一接口支持大规模分析查询，以研究知识图谱演变。
AI 中文摘要
知识图谱已成为整合异构数据和驱动下游任务（如问答、实体链接和语义搜索）的关键资源。它们以增量方式构建和维护，要么（i）完全自动化，例如YAGO；（ii）在社区监督下半自动进行，例如DBpedia；要么（iii）通过协作编辑手动完成，例如Wikidata。理解知识图谱的演变至关重要，因为变更可能反映现实世界的更新、错误修正或由破坏行为引入的噪声，所有这些都会影响下游应用的可靠性。在公开可用的知识图谱中，Wikidata是研究演变最具挑战性的案例，其拥有超过1.2亿个由人类和机器人编辑的实体，编辑历史跨越十多年。尽管Wikidata以各种格式（例如定期转储和实时事件流）公开变更数据，但没有任何格式支持对完整编辑历史进行分析性查询。因此，我们提出了WiDiff，一种从Wikidata的完整编辑历史中提取变更并提供统一接口以对其执行大规模分析性查询的工具。
英文摘要
Knowledge graphs have become a key resource for integrating heterogeneous data and powering downstream tasks such as question answering, entity linking, and semantic search. They are built and maintained incrementally, either (i) fully automated, e.g., YAGO, (ii) semiautomatically with community oversight, e.g., DBpedia, or (iii) manually through collaborative editing, e.g., Wikidata. Understanding the evolution of knowledge graphs is essential as changes may reflect real-world updates, error corrections, or noise introduced by vandalism, all of which affect the reliability of downstream applications. Among openly available knowledge graphs, Wikidata is the most challenging case to study evolution, with over 120 million entities edited by humans and bots and an edit history spanning more than a decade. Although Wikidata exposes change data in various formats (e.g., periodic dumps and real-time event streams), none support analytical queries over the complete edit history. Therefore, we present WiDiff, a tool that extracts changes from Wikidata's complete edit history and provides a unified interface for large-scale analytical queries over it.
