NDA 2016 : First International Workshop on Network Data Analytics
Call For Papers
Call for Papers: NDA 2016.
First International Workshop on Network Data Analytics
in conjunction with SIGMOD 2016
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
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
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
Shourya Roy, Xerox Research Centre India (Shourya.Roy@xerox.com)
Sameep Mehta, IBM Research India (firstname.lastname@example.org)
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.