Real world big data are largely dynamic, interconnected and unstructured text. To transform such massive unstructured data into structured knowledge is a common goal. Penn State News brought this interesting information to our attention in their article, “Talk to explore power of taxonomy and embedding in text mining.”
Equipped with domain-independent and domain-dependent knowledge-bases, it is possible to explore the power of massive data to transform unstructured data into structured knowledge. The data-driven approach could be promising at transforming massive text data into structured knowledge.
iawei Han, Michael Aiken Chair Professor in the Department of Computer Science at University of Illinois at Urbana-Champaign recently presented a talk as part of the Penn State Center for Socially Responsible Artificial Intelligence Distinguished Lecture Series. In the talk, Han discussed his work to explore the power of taxonomy and embedding in text mining. The talk was recorded and can be viewed here.
Melody K. Smith
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