[Lccd-internal] Fwd: Call for Papers: 2nd International Workshop on Network Data Analytics 2017

[Srijan Kumar]

---------- Forwarded message ----------
From: "Sharma, Raj" <Raj.Sharma2 at xerox.com>
Date: Nov 7, 2016 6:10 AM
Subject: Call for Papers: 2nd International Workshop on Network Data
Analytics 2017
To: "Sharma, Raj" <Raj.Sharma2 at xerox.com>
Cc:

**apologies, if you have received multiple copies of this email*



CALL FOR PAPERS

2nd International Workshop on Network Data Analytics 2017

Co-located with the ACM SIGMOD'17

May 19 2017, Raleigh, North Carolina, USA

Workshop Website: https://sites.google.com/site/networkdataanalytics2017/

Proceedings will be published by ACM





WORKSHOP

The Second International Workshop on Network Data Analytics (NDA 2017),
co-located with the ACM SIGMOD Conference 2017, is a forum for exchanging
ideas and methods for mining, querying and learning with (large-scale)
real-world networks, developing new common understandings of the problems
at hand, sharing of data sets where applicable, and leveraging existing
knowledge from different disciplines. This year, we have a special focus on
(1) research work pertaining to presence of noise in real-life graphs and
(2) novel applications of graph analytics in newer domains (like
transportation, education, retail/marketing, banking, healthcare etc.)
(preferably with demonstrations).



TOPICS OF INTEREST

Topics of interest include but not limited to the following:

- Core Graph Platform work which build on new age systems like Titan,
SPARK/GraphX, GraphLab/PowerGraph, Giraph, GraphChi 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

- Dynamic Graphs: Managing network updates; Analysing evolution and
detection of community structures in real-world graphs

- Querying and mining heterogeneous networks -- knowledge graphs etc.

- 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/Significant sub-graph mining, graph (sub)pattern matching

- Parallel graph processing techniques/architectures

- Game Theory, Social contagion and Information propagation with
applications in real-world networks:

        * Rumour proliferation

        * E-reputation; Viral Marketing

        * Disease propagation

        * Modelling traffic flow/spread

- Measuring graph characteristics–diameter, eigenvalues, triangle counting

- Noisy Graph Analytics:

        * Characterization and quantification of noise in real-life graphs

        * Benchmarking state-of-the-art algorithms on noisy graphs

        * Graph Noise Removal: Identification, reconstruction and cleaning

- Spatio-temporal analytics:

        * Streaming sensor data

        * Trajectory data

        * Time varying graphs -- road-networks, characterizing traffic
data, co-purchase networks, biological networks -- protein-protein and *
gene interaction networks etc.

- Novel Applications/Real-life experiences in Interesting Domains:

        * Social Networks; Citation Networks; Co-Purchase Networks

        * Biological Network Data; Ecological data

        * Retail, Marketing and Media

        * Financial Services and Business Data Analysis

        * Customer Care; Healthcare; Transportation data Cybersecurity



MOTIVATION

Networks are prevalent in today’s electronic world in a wide variety of
domains ranging from Engineering to Social Sciences, Life Sciences to
Physical Sciences, 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 a proliferation of
networks in new business domains like Telecommunications, Banking,
Retail/Marketing, Healthcare, Transportation 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.



Graphs are unarguably one of the most natural ways of 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.



IMPORTANT DATES

    Abstract Submission :January 9, 2017

    Paper Submission : January 16, 2017

    Notifications : March 6, 2017

    Camera Ready Submission : March 27, 2017

    Workshop Date : May 19, 2017

    All deadlines are 23:59 Hours PST



SUBMISSION GUIDELINES

Research papers submitted to NDA should present unpublished research papers
(full and short), demonstrations and case-studies in the broad area of
network/graph analytics as listed above. Submissions must follow the 2
column SIGMOD Proceedings Format, and should be double-blind. For templates
and details, please visit https://sites.google.com/site/
networkdataanalytics2017/submission-guidelines.



The workshop proceedings will be published by ACM.



SUBMISSION SITE

https://cmt3.research.microsoft.com/NDA2017



Keynote Speaker

Prof. Jiawei Han has kindly agreed to deliver an exciting keynote at the
workshop. The details will be posted later on the website.



Chaired by

Akhil Arora, Xerox Research, India

Shourya Roy, Xerox Research, India

Arnab Bhattacharya, IIT Kanpur, India



Contact

Email to:

arora.akhilcs at gmail.com, akhil.arora at xerox.com

shourya.roy at gmail.com, shourya.roy at xerox.com

arnabbhattacharya at gmail.com, arnabb at cse.iitk.ac.in
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