Harvesting and Querying the World’s Knowledge

January 20, 2011
Gjergji Kasneci | Mindswap on Data Intelligence

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. But isn’t this goal too ambitious, and didn’t the AI community fail on a similar goal (e.g. building expert systems)? What is the difference between the Semantic Web efforts and the AI efforts which, almost 30 years ago, lead to the “AI Winter”? These and many more questions will be addressed by this tutorial

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