Paper Submission
ICCSE’18 solicits original work submitted as a regular paper of up to 8 pages (inclusive of references) in ACM format (URL: http://www.acm.org/publications/proceedings-template). Accepted papers will appear in the ICCSE’18 Proceedings. The authors of a selected number of top quality papers will be invited to extend their papers for further review and possible publication in International Journal of Crowd Science or special issues of other reputable journals. Papers have to be submitted via the EasyChair submission page: https://easychair.org/conferences/?conf=iccse20182. For any inquiries, please write to iccse2018-2@easychair.org.
The ICCSE’17 Proceedings have been published in ACM Digital Library. Therefore, all papers included in the ICCSE’17 Proceedings are EI Indexed. The ICCSE’18 organizing committee shall continue to put up the request to ACM for the inclusion of the ICCSE’18 Proceedings in ACM Digital Library. If such request is approved by ACM, all papers included in the ICCSE’18 Proceedings will also be EI Indexed.
ICCSE’18 now invites you to participate and contribute to this international forum for the dissemination and exchange of up-to-date scientific information on theoretical and applied areas of CSE. The related fields and application areas relevant to ICCSE’18 include, but are not limited to:
| Theory: • Models and methods for Crowd Science and Engineering • Trust and incentives • The cloud and the crowd • Crowdsourcing • Mental model • AI (learning, reasoning and knowledge) • Big Data | Sensing: • Crowd sensing • Internet of Things • Intelligent sensing • Online sensing • Mobile sensing • Social sensing • Citizen sensing • Ubiquitous sensing • Smart city |
| Context: • Mobile context • Social context • Opportunity context • Trajectory context • Unobtrusive context • Context-aware algorithm • Context-aware representation • Context-aware reasoning • Context-aware recommendation • Machine learning for context awareness | Cognition: • Cognition based decision making • Online learning • Deep learning • Transfer learning • Temporal cognition • Perception • Attention • Memory • Affect, Behaviour and cognition • Analytics |
| Interaction: • Crowd AI • Crowd behaviour • Brain-computer interface • Harnessing the crowd in human-computer interaction • Crowdsourcing human-robot interaction • Human computation • Crowd mobilization • Crowd visualization • Emotion and personality | Practice: • Tools and platforms to support Crowd Science and Engineering • Crowd-sourced design and engineering • Massive Open Online Courses (MOOCs) • Citizen science • Digital sharing economy • Crowdfunding • Crowdsourcing well-being • Productive aging and e-healthcare • Gamification • Crowdsourcing in e-government • Industrial crowdsourcing |