The First Workshop on Data Mining for Smart Cities (DMCities 2015) will be held in conjunction with The IEEE International Conference on Data Mining series (ICDM) on 13 Nov 2015, in Atlantic City, New Jersey, USA.
Applying conventional data mining and machine learning methods in urban computing is non-trivial work. The urban data challenges ranges from handling the size and variety of urban data, to unravelling the complexity of the underlying physical models, to addressing the concerns on protecting individual’s privacy, etc. However, the past few years have seen significant advances in addressing such challenges by researchers who are stepping up their efforts in understanding the biology of cities using big data. It is our hope that through this workshop, the knowledge, experiences, and lessons can be shared to make data mining an essential and easy-to-use tool for the Smart City practioners.
Best Paper Award
All submitted papers are eligible for the Best Paper award. A cash award and certificate will be presented during the DMCities workshop.
•Paper Submission: July 20, 2015
•Notification: September 01, 2015
•Camera ready: September 18, 2015
•Workshop: November 13, 2015
Topics of Interest
We encourage submissions on all theoretical and practical aspects, as well as experimental studies of deployed systems. Topics of interests include (but are not limited to) the following subject categories:
•Data mining in pervasive environments
•Theories, algorithms and architectures for mining big data
•Social network analysis for citizen engagement and smart governance
•Data Semantics/ontology and integration for Smart City
•Streaming data mining for real time and/or quick response systems for smart healthcare and emergency management
•Data mining for improving public safety
•Housing supply/demand analysis using data mining
•Industrial and business analysis and mining
•Environmental modeling based on data mining methods
•Smart traffic system operations
•Data mining for population growth, aging and sustainability
•Integrated city planning using data mining
•Internet of Things (IoT) and smart cities
•Connected Vehicle (CV) technologies
•Visual analytics for city data
•Data security and privacy for utilizing urban-originated data
•Applications and Experiences of Smart City
DMCities2015 website: http://www.i2r.a-star.edu.sg/DMC...
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