posted by user: wangfengmadking || 2428 views || tracked by 3 users: [display]

MLG 2011 : Ninth Workshop on Mining and Learning with Graphs (MLG 2011)

FacebookTwitterLinkedInGoogle


Conference Series : Mining and Learning with Graphs
 
Link: http://www.cs.purdue.edu/mlg2011/index.html
 
When Aug 20, 2011 - Aug 21, 2011
Where San Diego, CA
Submission Deadline TBD
Categories    machine learning   data mining
 

Call For Papers

This year's Workshop on Mining and Learning with Graphs will be held in conjunction with the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining that will take place August 21-24, 2011 in San Diego, CA.
There is a growing need and interest in analyzing data that is best represented as a graph, such as the World Wide Web, social networks, social media, biological networks, communication networks, and physical network systems. Traditionally, methods for mining and learning with such graphs has been studied independently in several research areas, including machine learning, statistics, data mining, information retrieval, natural language processing, computational biology, statistical physics, and sociology. However, we note that contributions developed in one area can, and should, impact work in the other areas and disciplines. One goal of this workshop is to foster this type of interdisciplinary exchange, by encouraging abstraction of the underlying problem (and solution) characteristics during presentation and discussion.

In particular, this workshop is intended to serve as a forum for exchanging ideas and methods, developing new common understandings of the problems at hand, sharing of data sets where applicable, and leveraging existing knowledge from different disciplines. The goal is to bring together researchers from the related disciplines, including academia, industry and government, and create a forum for discussing recent advances in analysis of graphs. In doing so we aim to better understand the overarching principles and the limitations of our current methods, and to inspire research on new algorithms and techniques for mining and learning with graphs.

To reflect the broad scope of work on mining and learning with graphs, we encourage submissions that span the spectrum from theoretical analysis of methods, to algorithms and implementation, to applications and empirical studies. In terms of application areas, the growth of user-generated content on blogs, microblogs, discussion forums, product reviews, etc., has given rise to a host of new opportunities for graph mining in the analysis of Social Media. Social Media Analytics is a fertile ground for research at the intersection of mining graphs and text. As such, this year we especially encourage submissions on theory, methods, and applications focusing on the analysis of social media.

Related Resources

ICMLA 2019   18th IEEE International Conference on Machine Learning and Applications
IEEE ICDM 2019   ICDM 2019: The 19th IEEE International Conference on Data Mining
ICDMML 2019   【ACM ICPS EI SCOPUS】2019 International Conference on Data Mining and Machine Learning
IEEE BigData 2019   IEEE International Conference on Big Data
Special Issue on Learning from IoT Data 2019   ACM Transactions on Data Science: Special Issue on Retrieving and Learning from Internet of Things Data
Ei ISEEIE 2019   2019 2nd International Symposium on Electrical, Electronics and Information Engineering(ISEEIE 2019)
COMML 2020   International Conference on Optimization, Metaheuristics and Machine Learning
DSAA 2019   The 6th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2019)
WACV 2020   Workshop on Applications of Computer Vision
KSEM 2019   The 12th International Conference on Knowledge Science, Engineering and Management