posted by organizer: katak || 6009 views || tracked by 19 users: [display]

MUD 2015 : Mining Urban Data - Special Issue - Information Systems (Elsevier)

FacebookTwitterLinkedInGoogle

Link: http://goo.gl/vUejYf
 
When N/A
Where N/A
Submission Deadline Nov 30, 2014
Categories    data mining   machine learning   knowledge discovery
 

Call For Papers

===================================================================
Mining Urban Data - Special Issue - Information Systems (Elsevier)
===================================================================

# CALL FOR PAPERS
Submission Deadline: November 30, 2014 (*Extended*)
Link: http://goo.gl/vUejYf

# Scope
The establishment of innovative technologies related to mobile wearable computing and smart city infrastructures led to the generation of massive heterogeneous data streams. For example, sensors established in junctions can estimate the volume of traffic at a specific area. These sensors form networks that are able to track the vehicle flow of an entire city. Moreover, GPS sensors installed on public transport (e.g. buses) can create similar city pictures since delays can be tracked and utilized to monitor problems around the city. In addition, citizens constantly interact with mobile sensors in their smart-phones or use wearable technologies (e.g. in shoes) that track their activity. At the same time micro-blogging applications like Twitter provide a new stream of information that can be utilized to capture events, trends or sentiment. The purpose of this special issue to discuss the research challenges that arise due to the introduction of such data.

# Topics of Interest
Researchers are encouraged to submit papers focusing on the context of
"smart cities". Indicatively topics of interest are the following:
- Mining Streaming and Heterogeneous Data
- Big Data Management
- Mobile Data Management
- Sensor and Vehicular Networks
- Information Fusion
- Mining Mirco-blogs
- Noise, Uncertainty and Crowdsourcing
- Social Network Analysis
- Spatial Analysis and Visual Analytics

# Applications
- Disaster Management and Emergency Response
- Public Transport
- Energy Efficiency
- Event Detection
- Enabling and Improving Smart Cities
- Health
- Security

# Submission Guidelines
Authors should prepare their manuscript according to the Guide for Authors available from the online submission page of the Information Systems at http://ees.elsevier.com/is/. Authors must select "Mining Urban Data" when they reach the "Article Type" step in the submission process. All papers will be peer-reviewed following the Information Systems reviewing procedures.

# Guest Editors
- Ioannis Katakis, National & Kapodistrian University of Athens (Contact: katak@di.uoa.gr)
- Gennady Andrienko, Fraunhofer IAIS and City University London
- Dimitrios Gunopulos, National & Kapodistrian University of Athens
- Vana Kalogeraki, Department of Informatics, Athens University of Economics and Business
- Pedro Jose Marron, Universitat Duisburg-Essen
- Katharina Morik, Technische Universitat Dortmund
- Olivier Verscheure, IBM Research, Ireland
- Yannis Ioannidis, National & Kapodistrian University of Athens (Information Systems' Area Editor)

Related Resources

SCIS-ISIS 2022   Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems
MLDM 2022   18th International Conference on Machine Learning and Data Mining
IEEE IRI 2022   IEEE International Conference on Information Reuse and Integration for Data Science
ICML 2022   39th International Conference on Machine Learning
ABDAI 2022   2022 4th International Conference on Applications of Big Data and Artificial Intelligence(ABDAI 2022)
IEEE COINS 2022   IEEE COINS 2022: Hybrid (3 days on-site | 2 days virtual)
ABDAI-Sanya 2022   2022 4th International Conference on Applications of Big Data and Artificial Intelligence(ABDAI 2022)
WSCIS 2022   2022 3rd International Workshop on Smart City and Intelligent Systems (WSCIS 2022)
FAIML 2022   2022 International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML 2022)