Special Session on Advances in Data Science Theory and Interdisciplinary Applications – 5th International Conference on Communication, Management and Information Technology

In recent years, we testify an increasing amount of data in world history. More and

more data is becoming available at scale on the internet, smartphones, corporations,

or on the giant platforms such as Amazon. Data is transforming healthcare,

transportation, smart cities, business, and interpersonal social communication. The

need of data discovery constitutes new opportunities for building intelligent

systems. It is a scientific challenge to develop powerful methods and algorithms,

which improves the data collection, management, and extraction of relevant

knowledge from a large volume of data coming from heterogeneous sources and in

various formats. Machine learning techniques and data driven analytics could offer

significant improvements in the discovery and exploitation of data in different areas

and interdisciplinary applications.

This session aims to solicit high quality submissions on various aspects of Data

Acquisition (eg. IOT, sensors), Access to the information (eg. Databases, security

and privacy), Data Analytical techniques (eg. Machine learning, Natural language

processing), Data Visualization (eg. geospatial representations, social networks, data

mapping) and innovative Data Science Applications (eg. Smart communities,

healthcare, e-commerce). We invite submissions that describe novel methods to

address the challenges inherent to the following topics.

Topics of the Session:

 Data Science and Foundations

 Novel Theoretical / Computational Models for Data science

 Data and Information Quality

 New Data Standards

 Big Data Infrastructure

 Cloud/Grid/Stream Computing for Data Science

 High Performance/Parallel Computing Platforms

 Data Acquisition, Integration, Cleaning, and Best Practices

 Data Management

 Geospatial data Management

 Search and Mining of variety of data including scientific and engineering,

social, sensor/IoT/wearables, and multimedia data

 Data Search Architectures, Scalability and Efficiency

For additional information please visit www.iccmit.net