The 2nd University of Michigan
Workshop on Data, Text, Web, and Social Network Mining
Friday, April 22, 2011 (8:30 AM - 6 PM)
1670 CSE building
Sponsored by Yahoo!, CSE, and SI
- April 19, 2010: The complete workshop program is now available in PDF .
- April 19, 2011: The workshop is full!
Last year we had a big success with the University of Michigan
Workshop on Data, Text, Web, and Social Network Mining. We uncovered
lots of people at Michigan doing interesting and unexpected things
with data. It was such a big success, we'd like to try it again. In particular,
this year we will have a somewhat more practical bent, with more hands-on tutorials from on-campus experts.
Who is invited?
All UM faculty and graduate students working in the fields of text and
data mining, broadly construed to include models and technologies for
statistical data analysis, Web search technology, analysis of user
behavior, social network analysis, data visualization, etc. as well as
related areas. External visitors from the State of Michigan and beyond are also welcome to attend.
Sharad Goel, Senior Research Scientist, Yahoo!: Large-Scale Measurement of Human Behavior
The workshop consists of invited talk, faculty presentations, discussions, and a poster session.
- Morning Schedule
- 8:30 am to 9:00 am - Continental Breakfast in Tishman Hall
- 9:00 am to 9:20 am - Intro and Welcome
- 9:20 am to 9:40 am - Qiaozhu Mei, School of Information, University of Michigan
Towards the Next Generation of Search Engines for Electronic Health Records
- 9:40 am to 10:00 am - Honglak Lee, Computer Science and Engineering, University of Michigan
Unsupervised Learning of Sparse, Distributed, Convolutional Feature Representations
- 10:00 am to 10:20 am - Yongqun "Oliver" He, Microbiology and Immunology, University of Michigan Medical School
Ontology-Based Literature Mining
- 10:20 am to 10:40 am - Péter Érdi, Center for Complex Systems Studies, Kalamazoo College
Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network [Slides]
- 10:40 am to 10:55 am - break
- 10:55 am to 11:15 am - Matthew O'Donnell, English Language Institute, University of Michigan
VACNET: Extracting and Analyzing Non-Trivial Linguistic Structures at Scale [Slides]
- 11:15 am to 11:35 am - Jungkap Park, Mechanical Engineering, University of Michigan
Text and Image-Based Recognition and Extraction of Molecular Information from Figures and Figure Captions [Slides]
- 11:35 am to 11:55 am - Raj Rao Nadakuditi, Electrical Engineering and Computer Science, University of Michigan
New Twists on Eigen-Analysis (or Spectral) Learning [Slides]
- 11:55 am to 12:15 pm - Abe Gong, Gerald R. Ford School of Public Policy, University of Michigan
An Automated Snowball Census of the Political Web
- Afternoon schedule
- 12:15 pm to 1:15 pm - Lunch (Tishman Hall)
- 1:15 pm to 1:45 pm - Tutorial 1: Dragomir Radev, School of Information and Computer Science and Engineering
Tools for Natural Language Processing and Text Mining [Slides]
- 1:45 pm to 2:15 pm - Tutorial 2: Eytan Adar, School of Information and Computer Science and Engineering, University of Michigan
The Amazon Mechanical Turk for Big Data
- 2:15 pm to 2:45 pm - Tutorial 3: Matt Simmons, School of Information, University of Michigan
- 2:50 pm to 3:10 pm - KP Unnikrishnan, Center for Computational Medicine and Bioinformatics, University of Michigan
Network Discovery in Biology and Medicine through Data Mining
- 3:10 pm to 3:30 pm - David Ostrowski, Ford Motor Research
- 3:30 pm to 4:00 pm - break and Poster Session (1st floor, CSE)
- 4:00 pm to 5:00 pm - Invited Speaker: Sharad Goel, Yahoo! Research
Large-Scale Measurement of Human Behavior
- 5:00 pm to 5:10 pm - Q&A
- 5:15 pm to 6:00 pm - Poster Session Continues (1st floor, CSE)
Sharad Goel: Large-Scale Measurement of Human Behavior
With the increasing availability of network and behavioral data--from what we buy, to where we travel, to whom we know--we are now able to observe and quantify social processes to a degree that would have seemed impossible just a decade ago. These new microscopes into human activity not only have substantive implications for the social sciences, including economics, sociology, and psychology, but also raise challenging computational questions in large-scale data analysis. In this talk I'll present several illustrative examples from this emerging discipline of computational social science.