Untitled Document
Tenth International C* Conference on Computer Science & Software Engineering(C3S2E 2017)
July 24-26, 2017, Montreal, QC, Canada
Call for Papers:
C3S2E 2017[*] is the tenth in a series of annual international conferences addressing the needs of the academic community in computing science and software engineering. The objective of C3S2E is to meet annually to exchange ideas on current issues and focus on new challenges from both the theoretical and application aspects of CSE. C3S2E encourages the participation of practitioners from governmental and non-governmental agencies, industry, and academia not only from CSE but also from other disciplines with the potential of collaboration. The meeting offers participants a chance to broaden their insight into the multi-facets of CSE and emerging technologies while exploring R&D ideas in other disciplines as well, where CSE can make meaningful contributions.
Papers primarily based on (but not limited to) the following topics are welcome: (Topics include but not limited to)
- Computer science (e.g., AI, algorithms, NLP, computer graphics and vision, networking, gaming)
- Software engineering (e.g., MSR, empirical SE, software requirements, software architectures, software evolution, human interaction)
- Big Data, Data Analytics and Data science
- Knowledge systems (e.g., knowledge modeling, Semantic Web)
- Internet of Things (e.g., context awareness, sensor networks, Web services, smart devices)
IMPORTANT DATES:
- Papers submission deadline : April 10, 2017
- Acceptance notice and start of author early registration : June 2, 2017
- Author regular registration and Camera-ready upload to ConfSys deadline : June 30, 2017
User Name : Simon
Posted 28-02-2017 on 16:33:24 AEDT
Related CFPs
IJSPTM
International Journal of Security, Privacy and Trust Management
COMIT 2025
9th International Conference on Computer Science and Information Technology
IJCCMS
International Journal of Chaos, Control, Modelling and Simulation
BIGML 2025
6th International conference on Big Data, Machine learning and Applications