IDEAS2017 Conference - 12 - 14 July 2017
The 21st International Database Engineering and Applications Symposium IDEAS 2017 conference is to be hosted by UWE Bristol, England. In co-operation with ACM, ACM SIGKDD and ACM SIGMOD.
Call for Papers/Participation/Track (Targeted Session) Proposals
The annual IDEAS conference is a top international forum for data engineering researchers, practitioners, developers, and application users to explore revolutionary ideas and results, and to exchange techniques, tools, and experiences.
We invite participation of all interested in this meeting which provides an insight into original research contributions relating to all aspects of database engineering defined broadly, and particularly topics of emerging interest describing work on integrating new technologies into products and applications, on experiences with existing and novel techniques, and on the identification of unsolved challenges.
Track (Targeted Session) Proposals
As in the past, IDEAS 2017 will include tracks (Targeted Session) on current topics of interest to the community. If you and your colleagues would like to include such a track, please contact us ASAP (before 17 February 2017). Please include the topics, the track chair and the proposed addition to the program committee to handle the submissions for the track.
The paper submission for IDEAS 2017 would be via the pages on ConfSys.
This year, we are looking for organisers to manage, among
others, the following special tracks themes along with the main
event (General pool):
• Big Data Applications (e.g. Health, Environment, Transport)
• Data Sharing, Security and Privacy
• Smart Cities and Data Analytics
• Web and Cyber Security
- 17 February 2017: Track Proposals
- 24 March 2017: Papers submission deadline
- 26 May 2017: Notification of acceptance
- 25 June 2017: Camera-ready deadline
When submitting a paper, please select the appropriate track unless you are submitting to the main event (indicated by "General Pool").
Jiawei Han, Abel Bliss Professor, Department of Computer Science, University of Illinois at Urbana-Champaign
Title: Mining Structures from Massive Text Data: A Data-Driven Approach
Abstract: The real-world big data are largely unstructured, interconnected, and in the form of natural language text. One of the grand challenges is to turn such massive data into structured networks and actionable knowledge. We propose a text mining approach that requires only distant supervision or minimal supervision but relies on massive data. We show quality phrases can be mined from such massive text data, types can be extracted from massive text data with distant supervision, and relationships among entities can be discovered by meta-path guided network embedding. Finally, we propose a D2N2K (i.e., data-to-network-to-knowledge) paradigm, that is, first turn data into relatively structured information networks, and then mine such text-rich and structure-rich networks to generate useful knowledge. We show such a paradigm represents a promising direction at turning massive text data into structured networks and useful knowledge.
Prof Omer Rana, Cardiff University
The conference proceedings will be published by ACM in their
digital library; the ISBN assigned by ACM to IDEAS17 is to be
A version of the proceedings to be distributed to the conference attendees would be prepared by BytePress.
The conference organisers are the University of the West of England, Bristol, England and Concordia University, Montreal, Canada; with the cooperation of ACM, BytePress.org and ConfSys.org.
General chair: Bipin C. Desai, Concordia University, Montreal
Program chair: Dr Jun Hong, Queen's University Belfast
Local chair: Richard McClatchey, University of the West of England, Bristol
Publicity chair: Kamran Munir, University of the West of England, Bristol
IDEAS2017 Program committee
For more details see the main IDEAS2017 conference website.
IDEAS Steering committee
- Desai, Bipin C. (Chair), Concordia University
- Ng, Wilfred, Hong Kong University of Science and Technology
- Pokorny, Jaroslav, Charles University
- Toyoma , Motomichi, Keio University
- Ullman, Jeffrey, Stanford University