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Bled: Big Data/Data Science Track 2019 : 32nd Bled eConference : Humanizing Technology for a Sustainable Society (Big Data/Data Science Track) | |||||||||||||||
Link: http://bledconference.org/index.php/call-for-papers/#bigdata | |||||||||||||||
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Call For Papers | |||||||||||||||
The Bled eConference has been shaping electronic interactions since 1988. It attracts speakers and delegates from business, government, information technology providers and universities. It is the major venue for researchers working in all aspects of the digital transformation. With fresh ideas and complementary themes, we establish a creative environment for participants and an attractive meeting point for discussing new R&D and project ideas, for example in the spirit of Horizon 2020. The conference has a wide appeal, offering:
a fully-refereed Research Track and research in progress track, devoted to researchers in all aspects of digital transformation; Graduate Students Research Consortium, offering students to present their ongoing master’s and PhD study results; ePrototype Students Bazaar, offering students opportunities to present innovative e- or m-Business or Internet of Things ideas, models, prototypes and apps; a Business and Government Panel Track which attracts eminent business and government leaders from Europe, the Americas and Asia-Pacific; Business, Government and Academic Workshops and Meetings offering unparalleled opportunities to discuss, share and learn with colleagues from around the world; EU projects dissemination meetings; enabling project partners to connect with other similar projects and to disseminate results to a wider community. The Bled’s highlights: The conference is shaping electronic interactions since 1988 The conference theme is on Digital Transformation – Meeting the Challenges Strong relationships and cooperation with journals Coaching of PhD-students and postgraduates – Graduate Students Consortium and Students ePrototype Bazaar Research in progress and poster presentations Special interest tracks (besides regular tracks): eHealth Digital Wellness Blockchain Big Data/Data Science Education in the Digital Economy Business Models Smart Cities & Regions Security & Privacy ********************* Big Data/Data Science ********************* Propelled by computational power, the availability of (big and unstructured) data, major advancements in machine intelligence and unprecedented speeds at which analytics need to be generated and delivered, a wealth of new questions and opportunities arises in creating value to governmental bodies and businesses. As organizations transform into data and analytics centric enterprises, more research is needed not only on the technical aspects of analytics such as data science algorithms, computing infrastructure, but also on various other organizational issues in the business analytics context (e.g. managerial, strategic, leadership, data governance and inter-organizational issues). For this track, we invite technical, theoretical, design science, pedagogical and behavioral research as well as novel implementations of data analytics & visualization for varied data (or sources) such as sensors or Internet of Things (IoT) data, text, multimedia, business operations, clickstreams and user-generated content. We welcome papers examining a wide range of contexts including healthcare, security, energy, marketing, supply-chain, technology, service, hospitality, education, transportation, fraud prevention and the environment. Possible business-oriented topics of submissions include, but are not limited to: Big Data and Business Transformation Innovative Artefacts for Business Analytics Data Driven Business Modelling Data-Driven Process Mining and Innovation Data Strategy and Data Privacy Social and Ethical Issues in Big Data Social Impact of Data Science Competences in the Era of Big Data Data Science and Industry 4.0 Big Data Applications / Innovation Possible technical-oriented topics of submissions include, but are not limited to instantiations of: Data Mining / Machine Learning / Deep Learning Process Mining Data science Text & Multimedia analytics Social Network (Media) Analytics Real-time data analysis / Stream processing Internet of Things (IoT) / Sensor data analytics Spatial data analysis / Visualization Open Data / Data Sets |
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