Knowledge harvesting from text and Web sources

The proliferation of knowledge-sharing communities such as Wikipedia and the progress in scalable information extraction from Web and text sources has enabled the automatic construction of very large knowledge bases. Recent endeavors of this kind include academic research projects such as DBpedia, KnowItAll, Probase, ReadTheWeb, and YAGO, as well as industrial ones such as Freebase and Trueknowledge. These projects provide automatically constructed knowledge bases of facts about named entities, their semantic classes, and their mutual relationships. Such world knowledge in turn enables cognitive applications and knowledge-centric services like disambiguating natural-language text, deep question answering, and semantic search for entities and relations in Web and enterprise data. Prominent examples of how knowledge bases can be harnessed include the Google Knowledge Graph and the IBM Watson question answering system. This tutorial presents state-of-the-art methods, recent advances, research opportunities, and open challenges along this avenue of knowledge harvesting and its applications.

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