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<p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:11.0pt;font-family:"Times New Roman","serif"">The 9th International Conference on Big Data Technologies and Applications<o:p></o:p></span></b></p>
<p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:11.0pt;font-family:"Times New Roman","serif"">(BDTA-2018)<o:p></o:p></span></b></p>
<p class="MsoNormal" align="center" style="margin-bottom:6.0pt;text-align:center">
<span class="MsoHyperlink"><span style="font-size:11.0pt;font-family:"Times New Roman","serif"">URL: http://infoscale.org<o:p></o:p></span></span></p>
<p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:11.0pt;font-family:"Times New Roman","serif"">4-5 September 2018, Exeter, UK</span></b><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Selected papers will be invited to submit an extended version of their work to the journal special issues:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- ACM/Springer Mobile Networks and Applications Journal (MONET)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Concurrency and Computation: Practice and Experience<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Times New Roman","serif"">Introduction<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">============<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Due to the explosive evolution of Information Technology and Computer Science, we have entered in the Big Data Age, and this is really a scientific revolution, not just a
fashion. As always, the technological aspects evolve faster than the scientific community mentality. Transforming Big Data into Big Knowledge and developing a new kind of Knowledge-Based Systems require new visions and approaches. Companies, facing the Big
Data challenges, are moving faster in the right direction than the scientific community, being under a stronger competitive pressure. They were forced to renounce to wishful thinking, like the idea that a few variables, embedded in a few rules, discovered
usaing the old fashion statistics, will give intelligent support for business decisions. We have to do the same for developing various applications.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Moreover, motivated by the big data analytics needs, new computing and storage technologies are developing rapidly and pushing for new high-end hardware geared toward big
data problems. While the high-performance computing technologies have the potential to greatly improve the effectiveness of big data analytics, the cost and sophistications of those technology and limited initial application support often make them inaccessible
to the end users and not fully utilized in academia years later. Meanwhile, comprehensive analytic software environment and platforms, such as R and Python, have become increasingly popular open-source platforms for data analysis.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Also, Computational Intelligence (CI) methodologies, tailored to Big Data, and combined with a proper vision of living systems, e.g., as complex dynamical systems or networks
of interacting entities, could pave the way to Knowledge-Based System.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Potential topics of interest, which can be investigated from different perspectives (social, organizational, technological) include, but are not limited to, the following
application domains:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Data Visualization and Visual Analytics<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Natural Language Processing in Big Texts<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Biomedical imaging pre-processing and Analysis<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Hardware and Software solutions for Big Data Searching, Storing and Management<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Structured and Unstructured Data/Text/Web Mining<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Deep Learning architecture, representations, unsupervised and supervised algorithms<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Scalable computational intelligence tools<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Novel Computational Intelligence approaches for data analysis<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Evolutionary and Bio-inspired approaches for Big Data analysis<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- New domains and novel applications related to Big Data technologies<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Times New Roman","serif"">Important Dates<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">===============<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Submission deadline: 13 April 2018<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Notification deadline: 1 June 2018<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Camera-Ready deadline: 4 July 2018<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Times New Roman","serif"">Publication<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">===========<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">All accepted and presented papers will be published by Springer and made available through SpringerLink Digital Library.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">BDTA proceedings are indexed in leading indexing services, including Ei Compendex, ISI Web of Science, Scopus, CrossRef, Google Scholar, DBLP, as well as EAI’s own EU Digital
Library (EUDL).<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Authors of selected best accepted and presented papers will be invited to submit an extended version to:<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Mobile Networks and Applications (MONET) (IF:3.259)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">- Concurrency and Computation: Practice and Experience (IF:1.133)<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span lang="EN-US" style="font-family:"Times New Roman","serif"">Paper submission<o:p></o:p></span></b></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">================<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif"">Papers should be submitted through EAI ‘Confy‘ system (http://confy.eai.eu/entry.html), and have to comply with the Springer format (see Author’s kit section at
<a href="http://infoscale.org/authors-kit/">http://infoscale.org/authors-kit/</a>).<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p> </o:p></span></p>
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