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IWcee18 VI International Workshop on Computational Economics and Econometrics
Rome, June 26-28, 2018
Machine Learning, Artificial Intelligence and Big Data: Methods and New Perspectives for Research and Society more info: https://sites.google.com/view/iwcee18/home
The last few years have witnessed an unprecedented production and availability of information on many aspects of social and economic life. Huge datasets on people and institutions, detailed spatial and relational data, vast collection of new figures on health-related subjects, data collection from the web and mobile devices, are in an impressive surge. The related increase in computing power and algorithm development, and the need to “turn information into knowledge”, has promoted a proliferation of new research on the intersection between data science, statistics, computer science and artificial intelligence both at academic and industry level. The intermingling development of hardware and software solutions is pushing forward the ability to produce sophisticated tangible and intangible artifacts able to learn from experience and/or extract value from data. How can big data and machine learning revolution help to address societal “big challenges”? How can we improve our capacity to extract “knowledge” form “information”? What specific methods are suitable for addressing thought-provoking research questions in this area of research? How can we reduce uncertainty and increase predictive power within complex socio-economic systems? IWcee18 aims at attracting papers dealing with previous challenging questions, thus promoting an open scientific debate within the attending community. Papers on (but not limiting to) the following and related subjects are welcome:
IWcee18 will publish the best papers in a Special Issue of “The International Journal of Computational Economics and Econometrics” (IJCEE). (http://www.inderscience.com/ijcee). IJCEE is indexed in: Scopus (Elsevier), Emerging Sources Citation Index (Clarivate Analytics), Chartered Association of Business Schools (CABS) Academic Journal Guide
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