The topics of Web Intelligence (WI) have received increasing interest in the past years. They comprise many fields, such as collective intelligence, data science, human-centric computing, knowledge management, and network science. WI‘17 aims to cover leading research that both deepens the understanding of computational, logical, cognitive, physical as well as business and social foundations of the future Web, and enables the development and application of intelligent technologies.
The research track of WI’17 invites original high-quality papers. WI’17 is methodologically open, i.e. conceptual, empirical as well as theoretical and technical papers are welcome.
Topics and Areas
Paper Submission and Publication
WI’17 solicits original work submitted as a regular paper, limited to 6-8 pages, in ACM 2-column format. Each paper will be peer-reviewed by at least three PC members on the basis of technical quality, relevance, originality, significance and clarity. Accepted papers will be published in the conference proceedings by ACM and indexed by EI. Furthermore, selected WI’17 papers will be invited to submit extended versions for publication in Web Intelligence journal and other international journals.
Papers have to be submitted via the cyberchair submission page and according to the rules specified on this page:
Call for Tutorials/Workshops/Special-Sessions
In addition to the research track, WI’17 comprises special sessions and workshops as well as tutorials and a PhD mentoring session. Moreover, industry papers and demo proposals can be submitted to WI’17 and will be dealt with by a special PC for industrial papers which will apply industry-compliant assessment criteria.
In all cases please refer to the individual call for papers on http://webintelligence2017.com/participants/.
Best Paper awards will be conferred at the conference on the authors of (1) the best research paper, (2) the best student paper. Application-oriented submissions will be considered for the best application paper award.
WI’17 PC Co-Chairs
PCChair [at] webintelligence2017 [dot] com
Rainer Alt, Leipzig University, Germany
Xiaohui Tao, University of Southern Queensland, Australia