Call for paper

  Research in mobile and social computing environments is now turning to novel concepts to address the challenge of data processing and analysing. The MWDA2017 workshop addresses issues of data management in mobile and social computing environments with a special focus on data processing. The goal of the workshop is to build a forum for researchers from academy and industry to investigate challenging and innovative research issues in the subject, which combines data analytics within mobile and social environment and to explore creative concepts, theories, innovative technologies and intelligent solutions. We intend this workshop to act as an initial place where people from different areas can find a forum to discuss issues of data management and processing in new and emerging mobile computing environments. Potential participants may come from communities of mobile computing, social computing, or any other areas related to data mining, processing and analysing and etc., in order to present their state-of-the-art progress and visions on the various overlaps across those disciplines.

Workshop topics

  • Activity Recognition in Pervasive and Ubiquitous Environments

  • Big Data Ming in Mobile Social Networks

  • Mobile Cloud Computing Techniques for Big Data

  • Variation-Aware Data Analytics and High-Speed Data Stream Mining in Ubiquitous Environment

  • Mining Mobility Social Media for Information about Health or Finance

  • Identifying Sentiment and Emotion towards Mobile Products and Services

  • Identifying the Holder and the Object of the Sentiment

  • Deep learning for Semantic Solutions and Its Applications in Mobile and Social Media Data Mining

Paper Submission

  Submissions must not exceed 10 pages in LNCS format, including references. All submissions must be in PDF format. Authors should avoid the use of non-English fonts to avoid problems with printing and viewing the submissions. All accepted papers MUST follow strictly the instructions for LNCS Authors. Springer LNCS site offers style files and information:

Submission website:  .