1. The proceeding of DaEng-2013 will be published by the renowned Lecture Notes in Electrical Engineering (LNEE) by Springer Verlag (Confirmed).
2. The venue of DaEng-2013 has been updated!
4. For participant (non presenter), please register HERE!
5. Papers submission is CLOSED!
7. We will send all materials of accepted and registered to Springer in the middle of October, 2013! Therefore, please register and make a payment on/before October 12, 2013!
8. The final conference program and parallel schedule have been finished by program chair.
Data engineering refers to the use of engineering techniques and methodologies in the design, development and assessment of computer systems for different computing platforms and its applications. With the different forms of data and its rich semantics, the need for sophisticated techniques has resulted an in-depth content processing, engineering analysis, indexing, learning, mining, searching, management, and retrieval of data, and to identify new issues and directions for future research and development work.
The First International Conference on Advanced Data and Information Engineering (DaEng-2013) is dedicated to address the challenges in the areas of database, information retrieval, data mining and knowledge management, thereby presenting a consolidated view to the interested researchers in the aforesaid fields. The conference looks for significant contributions to advances on data and information engineering in theoretical and practical aspects.
The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on advanced on data engineering concepts and establishing new collaborations in these areas.
The event will be held over three days, with presentations delivered by researchers from the international community, including presentations from keynote speakers and scientific parallel session presentations.
Data Engineering (DaEng) Research Center
Applied Mathematics and Computer Science (AMCS) Research Center
Soft Computing and Data Mining Research Group, FSKTM UTHM
To be announced