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Searching for Knowledge Instead of Web Pages

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The rapid information growth on the Web calls for knowledge-oriented and context-aware search techniques that aim at retrieving knowledge fragments instead of Web pages. Inspired by the advent of knowledge sharing communities such as Wikipedia and the progress of information extraction, various scientific and industrial efforts are aiming at turning the Web into the world’s most comprehensive knowledge base. This goal involves various tasks such as information extraction, knowledge representation, ontology construction, searching and ranking at entity-relationship level, and many more. The talk will give an overview of the YAGO -NAGA approach to the above tasks.

This talk is part of the Machine Learning @ CUED series.

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