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 talk discusses state-of-the-art methods, research opportunities, and open challenges
along this avenue of knowledge harvesting.
Jennifer Müller, 06/25/2010 16:28
Jennifer Müller, 06/24/2010 15:56
Jennifer Müller, 02/23/2010 13:02
Anna-Lisa Overhoff, 02/17/2010 14:06 -- Created document.