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CS Colloquium: Xiang Ren (UIUC) - Effort-Light StructMine: Turning Massive Corpora into Structures
Thu, Feb 23, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
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.
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.
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 ï¼DAISï¼Research 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
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
