Canberra Data Miners: Seminar on Text, Knowledge and Information Extraction, by Dr Lizhen Qu (NICTA), Canberra, 4:30-5:30pm, Tuesday 1 Sept

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Topic: Text, Knowledge, and Information Extraction
Speaker: Dr. Lizhen Qu, Researcher at NICTA
Organizer: Canberra Data miners Meetup Group
Date and time: 4:30-5:30pm, Tuesday 1 Sept
Location: Teal Room of Inspire Centre, University of Canberra, Building 25, University of Canberra, Pantowora St, Bruce
RSVP URL:  http://www.meetup.com/CanberraDataMiners/events/224420305/

Abstract:

Unstructured text is exploding at an astounding rate. Managing documents, mining interesting information from text, making decisions based on large volume of text impose a big challenge in this era. One solution is to apply information extraction (IE) techniques, which map unstructured text into structured knowledge representation, and store them into existing databases or knowledge bases. Then we can apply existing data analytics tools based on structured data for diverse purposes. In this talk, I will walk you through the core IE techniques such as named entity recognition, named entity disambiguation, and relation extraction, as well as their real-world applications. I will also cover our ongoing work regarding harvesting domain specific knowledge by using deep learning techniques.

Bio:

Dr. Lizhen Qu is currently a researcher at the Machine Learning Research Group of National ICT Australia (NICTA), a research fellow at Australian National University. He was an invited speaker at Machine Learning Summer School in Sydney in 2015. Prior to being employed at NICTA, Lizhen Qu was a post-doc at Max Planck Institute for Informatics. Dr. Qu completed his PhD doctorate qualification in Sentiment Analysis from Max Planck Institute for Informatics and University of Saarland.  In 2008, he received the Diploma degree from the Computer Science Department at Technical University of Kaiserslautern. His main research focus is in natural language processing (NLP), with particular emphasis on machine learning approaches. He is especially interested in devising deep learning models to extract structured representations of knowledge from unstructured text. More details about Dr. Qu can be found at https://www.nicta.com.au/category/research/machine-learning/people/lqu/.

Contact:
Yanchang Zhao
Organizer of Canberra Data Miners Group
Email: yanchang@rdatamining.com

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