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Events for May 16, 2014
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2014 Mork Family Department Commencement Reception
Fri, May 16, 2014 @ 12:15 PM - 02:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Receptions & Special Events
Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116
Audiences: Graduating Students, Family, Faculty, and Staff
Contact: Ryan Choi
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USC Viterbi Master's Commencement Ceremony
Fri, May 16, 2014 @ 03:00 PM - 05:00 PM
USC Viterbi School of Engineering
Student Activity
Please note: Only Fall 2013, Spring 2014, and Summer 2014 graduates may participate in the May 16, 2014 Masterââ¬â¢s Commencement Ceremony. We apologize that we are unable to accommodate graduates from other semesters.
MASTERS STUDENTS: Please proceed to the fire lane (located on McCarthy Way) for check-in and line up at 2:00 pm.
PARENTS & GUESTS: Please enter the Galen Center through the entrance located on the corner of Jefferson & Figueroa.
All Graduates should choose a location on campus to meet your families after the ceremony. This will help us remain respectful to the commencement ceremony following ours. NO ONE will be permitted to linger inside or outside of the Galen Center after the ceremony
For information regarding parking please visit: http://commencement.usc.edu/parking-information/
To register for the ceremony and for more info visit: https://gapp.usc.edu/about/events/usc-viterbi-masters-commencement-ceremony.Location: Galen Center
Audiences: Graduate
Contact: Meredith Tiras
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NL Seminar- Story-Level Inference to Improve Machine Reading
Fri, May 16, 2014 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Hans Chalupsky, USC/ISI
Talk Title: Story-Level Inference to Improve Machine Reading
Series: Natural Language Seminar
Abstract: Extracting well-defined entities and relations that hold between them from unstructured text is an important prerequisite for a variety of tasks such as knowledge base population, question answering, data analytics, visualization, etc. The difficulty of this problem is evidenced by the annual TAC-KBP evaluations organized by NIST, where the best-performing systems in the slot-filling task still only achieve an f-value in the high 30's. These high error rates on individual relations get further compounded once relations have to be joined to answer a question.
State-of-the art statistical information extraction techniques focus primarily on the phrase and sentence level to extract entities and relations between them, and are generally ignorant of the greater context around them. We present a new approach which aggregates locally extracted information into a larger story context and uses abductive reasoning to generate the best story-level interpretation. We demonstrate that this approach can significantly improve relation extraction and question answering performance on complex questions. We will also describe ongoing work to apply this type of inference to the TAC Knowledge Base Population task in order to improve relation extraction and coreference resolution.
Biography: Hans Chalupsky is a project leader at the Information Sciences Institute of the University of Southern California, where he leads the Loom Knowledge Representation and Reasoning Group. He holds a Master's degree in computer science from the Vienna University of Technology, Austria and a Ph.D. in computer science from the State University of New York at Buffalo. Dr. Chalupsky has over 25 years of experience in the design, development and application of knowledge representation and reasoning systems such as PowerLoom, and he is the principal architect of the KOJAK Link Discovery System. His research interests include knowledge representation and reasoning systems, natural language processing, knowledge and link discovery, anomaly detection and semantic interoperability.
Host: Aliya Deri and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
