Psychiq and Wwwyzzerdd: Wikidata completion using Wikipedia

IF 3 3区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Semantic Web Pub Date : 2023-09-12 DOI:10.3233/sw-233450

Daniel Erenrich

引用次数: 0

Abstract

Despite its size, Wikidata remains incomplete and inaccurate in many areas. Hundreds of thousands of articles on English Wikipedia have zero or limited meaningful structure on Wikidata. Much work has been done in the literature to partially or fully automate the process of completing knowledge graphs, but little of it has been practically applied to Wikidata. This paper presents two interconnected practical approaches to speeding up the Wikidata completion task. The first is Wwwyzzerdd, a browser extension that allows users to quickly import statements from Wikipedia to Wikidata. Wwwyzzerdd has been used to make over 100 thousand edits to Wikidata. The second is Psychiq, a new model for predicting instance and subclass statements based on English Wikipedia articles. Psychiq’s performance and characteristics make it well suited to solving a variety of problems for the Wikidata community. One initial use is integrating the Psychiq model into the Wwwyzzerdd browser extension.

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Psychiq和Wwwyzzerdd:使用维基百科完成维基数据

尽管规模庞大，维基数据在许多领域仍然不完整和不准确。英文维基百科上成千上万的文章在维基数据上没有或只有有限的有意义的结构。文献中已经做了很多工作来部分或完全自动化完成知识图的过程，但很少实际应用于维基数据。本文提出了两种相互关联的实用方法来加快维基数据完成任务。第一个是Wwwyzzerdd，这是一个浏览器扩展，允许用户快速从维基百科导入语句到维基数据。Wwwyzzerdd已被用于对维基数据进行超过10万次的编辑。第二个是Psychiq，一个基于英文维基百科文章预测实例和子类陈述的新模型。Psychiq的性能和特点使它非常适合为维基数据社区解决各种问题。一个最初的用途是将Psychiq模型集成到Wwwyzzerdd浏览器扩展中。

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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来源期刊

Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

8.30

自引率

6.70%

发文量

期刊介绍： The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.