posted by organizer: shouryaroy || 2396 views || tracked by 3 users: [display]

NDA 2016 : First International Workshop on Network Data Analytics

FacebookTwitterLinkedInGoogle

Link: https://sites.google.com/site/networkdataanalytics2016/
 
When Jul 1, 2016 - Jul 1, 2016
Where San Francisco, California
Abstract Registration Due Feb 5, 2016
Submission Deadline Feb 12, 2016
Notification Due Mar 31, 2016
Final Version Due Apr 29, 2016
Categories    graph mining   graph query   graph systems
 

Call For Papers

Call for Papers: NDA 2016.

First International Workshop on Network Data Analytics
https://sites.google.com/site/networkdataanalytics2016/submission-and-dates

in conjunction with SIGMOD 2016
http://www.sigmod2016.org/org_sigmod_workshops.shtml

Scope and Overview

Networks are prevalent in today’s electronic world in a wide variety of domains ranging from Engineering to Social Sciences, Life Sciences to Data Analytics and so on. Researchers and practitioners have studied networks in multiple ways like defining network metrics, providing theoretical results and examining problems like pattern mining, link prediction etc. Recently, we have witnessed proliferation of networks in new business domains like Telecommunications, Banking, Retail, Healthcare etc. Most of these real-world applications give rise to networks which exhibit unique and interesting structures supporting multiple dynamical processes that shape these networks over time. Owing to the tremendous pace of growth of electronic data many of these networks are also evolving at a rapid pace leading to evolving networks.

Graphs are a popular representation for such data because of their ability to represent different entity and relationship types, including the temporal relationships necessary to represent the dynamics of a data stream. However, fusing such heterogeneous data into a single graph or multiple related graphs and mining is challenging task.Emerging massive data has made calls for fundamental change to graph data modelling and programming paradigm. APACHE SPARK is one such successful instantiation. Finally, it is interesting to see the applicability of graph based techniques by applying them to even wider range of data like spatial, spatio-temporal and IOT data which did not inherently exhibit network structure by modelling relationships.

This workshop is a forum for exchanging ideas and methods for mining and learning with networks, 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 academia, industry, and government, to create a forum for discussing recent advances graph analysis. Towards that we would like to encourage applications and demonstrations of relevant real-life systems and research prototypes.


Topics of Interest

Topics of interest include but not limited to the following. Along with novel research work, we encourage submissions with demonstrations and case studies from real-life experiences in various domains such as Social Networks, Biological Network Data, Marketing and Media, Business Data Analysis, Healthcare Data, Cybersecurity etc.

- Core Graph Platform work which build on new age systems like Titan, SPARK, Giraph etc
- Network representation, storage, indexing and querying methods
- Graph query languages, visualization techniques and querying interfaces
- Benchmarking RDF/SPARQL, Titan/Gremlin and/or graph database systems
- Managing network updates, evolving and heterogeneous graphs
- Graph summarization and sampling
- Machine learning techniques such as clustering, classification, semi-supervised learning, spectral techniques, and kernel methods in the context of networks
- Frequent subgraph mining, graph pattern matching
- Parallel graph processing techniques/architectures
- Game Theory in Social Networks and Social Contagion
- Measuring graph characteristics–diameter, eigenvalues, triangle counting

Paper Submission:
Authors are invited to submit original, unpublished research papers. Papers must follow the SIGMOD Proceedings Format. Submitted papers should be maximum 8 pages in length, including references and appendix. Submissions will be handled through EasyChair - https://easychair.org/conferences/?conf=nda2016


Important Dates
Abstract Submission :February 5, 2016
Paper Submission : February 12, 2016
Notifications : March 31, 2016
Camera Ready Submission : April 29, 2016
Workshop dates : July 1, 2016

Workshop Chairs
Shourya Roy, Xerox Research Centre India (Shourya.Roy@xerox.com)
Sameep Mehta, IBM Research India (sameepmehta@in.ibm.com)

Program Committee:
Ambuj Singh, University of California at Santa Barbara
Amol Deshpande, University of Maryland
Amol Ghoting, GraphSQL
Arijit Khan, ETH Zurich
Francesco Bonchi, Yahoo Labs Barcelona
H V Jagadish, University of Michigan
Haggai Roitman, IBM Research
James Cheng, The Chinese University of Hongkong
Kavitha Srinivas, IBM Research
Medha Atre, Independent Researcher
Prasenjit Mitra, QCRI
Sayan Ranu, Indian Institute of Technology Madras
Sihem Amer-Yahia, Laboratoire d’Informatique de Grenoble
Srikanta Bedathur, IBM Research
Srinivasan Parthasarathy, The Ohio State University

For any queries, please email Workshop Chairs.

Related Resources

From Data to Decision: Empowering Ecosys 2025   The International Society for Ecological Modelling Global Conference:
BIDA 2025   2nd International Conference on Business Intelligence and Data Analytics
DEBS 2025   The 19th ACM International Conference on Distributed and Event-Based Systems (DEBS 2025)
AIPIDAY 2025   AI on Pi Day
ICoSR 2025   2025 4th International Conference on Service Robotics
AMLDS 2025   IEEE--2025 International Conference on Advanced Machine Learning and Data Science
SPIE-Ei/Scopus-DMNLP 2025   2025 2nd International Conference on Data Mining and Natural Language Processing (DMNLP 2025)-EI Compendex&Scopus
IEEE DSIT 2024   2024 IEEE 7th International Conference on Data Science and Information Technology (DSIT 2024)
ACM SAC 2025   40th ACM/SIGAPP Symposium On Applied Computing
IJCNN 2025   International Joint Conference on Neural Networks