Fei Wang: Associate Professor, Department of Computer Science and Engineering, UConn.
Hanghang Tong (Main Contact): Assistant Professor, School of Computing, Informatics and Decision Systems Engineering, ASU.
Munmun De Choudhury: Assistant Professor, School of Interactive Computing, Georgia Institute of Technology.
Zoran Obradovic: Laura H. Carnell Professor, Computer and Information Sciences Department, Temple University.
Yu Cheng: Research Staff Member, IBM T.J. Watson Research Center, NY.
Liangyue Li: PhD Student, ASU.
13:40-14:40pm: Invited Talk by Prof. Chandan Reddy: Survival Regression and Transfer Learning Methods for Patient Risk Prediction
14:40-15:00pm: Regular Paper Presentation: Janani Kalyanam, Sumithra Velupillai, Son Doan, Mike Conway and Gert Lanckriet. Facts and Fabrications about Ebola: A Twitter Based Study
15:00-15:30pm: Coffee Break
15:30-16:30pm: Invited Talk by Prof. Shuiwang Ji: Big Data Analytics for Brain Science
16:30-16:50pm: Regular Paper Presentation: Pradeeban Kathiravelu and Ashish Sharma. MEDIator: A Data Sharing Synchronization Platform for Heterogeneous Medical Image Archives
16:50-17:10pm: Regular Paper Presentation: Roberto Souza, Denise Brito, Renato Assuncao and Wagner Meira Jr. A latent shared-component generative model for real-time disease surveillance using Twitter data
17:10-17:20pm: Conclusion and Workshop Closing
The emergence of big data and network science has been changing the landscape where people live and interact with each other. This well-connected world has proposed novel requirements on the transforming healthcare from reactive and hospital-centered to preventive, proactive, evidence-based, person-centered and focused on well-being rather than disease. Various types of data are involved in this broader context of healthcare:
Clinical data, mainly the patient records from clinical institutions, such as medical imaging, patient electronic health records, clinical trial data, etc.
Genotype data, basically the genetic makeups of the individuals, such as DNA and protein.
Social media data, which is the information the individuals posted on online social platforms such as Facebook, Twitter, Patientslikeme, etc.
Environmental sensory data, which are the information sampled from the surrounding environment where the individuals are living in, such as air pollution and humidity information.
Behavioral and sentiment data, which could be the data recorded by the wearable devices on patient’s activities
Mobile data, which are sampled from individuals’ mobile devices
Integrating all those different kinds of information to make people healthier is a problem of vital importance and requires a lot of efforts from different parties where data miners play a major role. This makes this workshop highly relevant to KDD, the premier conference of data mining. Moreover, the National Science Foundation of United States set up a novel program on smart and connected health [link], which makes this workshop an in-time event for people to share their opinions and experiences on this topic.
This workshop will bring together the interdisciplinary researchers from academy, research labs and practice to share, exchange, learn, and develop preliminary results, new concepts, ideas, principles, and methodologies on applying data mining technologies to make people healthier in such connected world. Any researchers and practitioners are welcome to attend, no specific background knowledge is required.
The topics of this workshop include, but not limit to, the following:
Integration and matching of different data sources
Quality assessment and improvement of different data
Disease modeling and early intervention
Data-drive methods for personalized medicine
Care coordination and pathway analysis
Behavioral modeling and sentiment analysis
Mobile health
Social media and public health
Comprehensive risk prediction
Community based elder care
Large scale and longitudinal analysis of multi-faceted information
Visual analytics and interactive computation
Submitted manuscripts must be formatted in ACM 2-column format (4~6 pages, the same templates as KDD main conference) and submitted through this site. Each submission will be reviewed by at least three program committee members. At least one of the authors of every accepted paper must register and present their work at KDD 2015 workshop venue. The BigChat 2015 organization committee will select one paper of the highest quality to receive the BigChat 2015 best paper award. The Winner will receive a certificate together with a cash honoarium.
Important Dates
Submission Date: June 5th, 2015
Notification Date: June 30th, 2015
Camera-ready: July 15th, 2015
Workshop date: August 10th, 2015
Yongjie Cai, City University of New York
Prudhvi Janga, Amazon
Jiming Liu, Hong Kong Baptist University
Robert Moskovitch, Ben-Gurion University
Niels Peek, Universit of Manchester
Chandan Reddy, Wayne State University
Gregor Stglic, University of Maribor
Xing Su, City University of New York
Zhaonan Sun, IBM T.J. Watson Research Center
Vincent S. Tseng, National Chiao Tung University
Jieping Ye, Arizona State University
Xiang Zhang, Case Western Reserve University
Jiayu Zhou, Samsung Research North America
Kunpeng Zhang, University of Maryland, College Park
It's a half-day workshop.
URL: BigCHat at KDD 2014
Other related events by workshop organizers: ACM Transactions on Knowledge Discovery from Data (TKDD) Special Issue on Connected Health at Big Data Era