From information to knowledge: harvesting entities and relationships from web sources

There are major trends to advance the functionality of search engines to a more expressive semantic level. This is enabled by the advent of knowledge-sharing communities such as Wikipedia and the progress in automatically extracting entities and relationships from semistructured as well as natural-language Web sources. Recent endeavors of this kind include DBpedia, EntityCube, KnowItAll, ReadTheWeb, and our own YAGO-NAGA project (and others). The goal is to automatically construct and maintain a comprehensive knowledge base of facts about named entities, their semantic classes, and their mutual relations as well as temporal contexts, with high precision and high recall. This tutorial discusses state-ofthe-art methods, research opportunities, and open challenges along this avenue of knowledge harvesting. Categories and Subject Descriptors

• Type: Conference
• Year: 2010
• Where: PODS
• Authors: Gerhard Weikum, Martin Theobald
• Keywords: Database, Expressive Semantic Level, Kind Include Dbpedia, Natural-language Web Sources, PODS 2010