BEGIN:VCALENDAR BEGIN:VEVENT SUMMARY:CS Colloquium: Xiang Ren (UIUC) - Effort-Light StructMine: Turning Massive Corpora into Structures DESCRIPTION:Speaker: Xiang Ren, UIUC Talk Title: Effort-Light StructMine: Turning Massive Corpora into Structures Series: CS Colloquium Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium. \n \n The real-world data, though massive, are hard for machines to resolve as they are largely unstructured and in the form of natural-language text. One of the grand challenges is to turn such massive corpora into machine-actionable structures. Yet, most existing systems have heavy reliance on human effort in the process of structuring various corpora, slowing down the development of downstream applications. \n \n In this talk, I will introduce a data-driven framework, Effort-Light StructMine, that extracts structured facts from massive corpora without explicit human labeling effort. In particular, I will discuss how to solve three StructMine tasks under Effort-Light StructMine framework: from identifying typed entities in text, to fine-grained entity typing, to extracting typed relationships between entities. Together, these three solutions form a clear roadmap for turning a massive corpus into a structured network to represent its factual knowledge. Finally, I will share some directions towards mining corpus-specific structured networks for knowledge discovery. Biography: Xiang Ren is a Computer Science PhD candidate at University of Illinois at Urbana-Champaign, working with Jiawei Han and the Data and Information System (DAIS)Research Lab. Xiang's research develops data-driven methods for turning unstructured text data into machine-actionable structures. More broadly, his research interests span data mining, machine learning, and natural language processing, with a focus on making sense of massive text corpora. His research has been recognized with a Google PhD Fellowship, Yahoo!-DAIS Research Excellence Award, C. W. Gear Outstanding Graduate Student Award, and has been transferred to US Army Research Lab, NIH, Microsoft, Yelp and TripAdvisor. Host: CS Department DTSTART:20170223T110000 LOCATION:RTH 217 URL;VALUE=URI: DTEND:20170223T122000 END:VEVENT END:VCALENDAR