Abstract

Recent advances in scalable information extraction from Web sources has enabled the automatic construction of large knowledge bases, such as DBpedia, EntityCube, KnowItAll, ReadTheWeb, and YAGO-NAGA. In this tutorial, we explain how these knowledge bases are organized, how they are constructed, how they can be maintained and extended in structure and contents, and how they serve as enabling assets for semantic applications. 2 Longer Description The advent of knowledge-sharing communities such as Wikipedia and the progress in scalable information extraction from Web sources has enabled the automatic construction of large knowledge bases. Recent endeavors of this kind include academic research projects such as DBpedia, EntityCube, KnowItAll, ReadTheWeb, and YAGO-NAGA, as well as industrial ones such as Freebase and Trueknowledge. These projects provide automatically-constructed, large and rich knowledge bases of facts about named entities, their semantic classes, and their mutual relations. This 1-day tutorial discusses a) the content, organization, and potential of these Webinduced knowledge bases, b) state-of-the-art methods for constructing them from semistructured and textual Web sources, c) recent approaches to maintaining and extending them, which includes introducing a temporal dimension of knowledge, d) use cases of knowledge bases, including semantic search, reasoning for question

Citations