By Khalid Saeed, Wladyslaw Homenda
This booklet constitutes the complaints of the fifteenth IFIP TC8 overseas convention on computing device info structures and business administration, CISIM 2016, held in Vilnius, Lithuania, in September 2016.
The sixty three usual papers offered including 1 inivted paper and five keynotes during this quantity have been conscientiously reviewed and chosen from approximately 89 submissions. the most themes coated are tough set equipment for large information analytics; photographs, visualization, category; optimization, tuning; scheduling in production and different functions; algorithms; judgements; clever disbursed platforms; and biometrics, id, security.
Read or Download Computer Information Systems and Industrial Management: 15th IFIP TC8 International Conference, CISIM 2016, Vilnius, Lithuania, September 14-16, 2016, Proceedings PDF
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Additional resources for Computer Information Systems and Industrial Management: 15th IFIP TC8 International Conference, CISIM 2016, Vilnius, Lithuania, September 14-16, 2016, Proceedings
J. Adv. Math. Appl. 1, 61–73 (2012) 30. : Rough set based reasoning about changes. Fundamenta Informaticae 119(3–4), 421–437 (2012) 31. , Suraj, Z. ): Rough Sets and Intelligent Systems. Professor Zdzislaw Pawlak in Memoriam. Series Intelligent Systems Reference Library, vol. 42-43. Springer, Heidelberg (2013) 32. Sun, R. ): Cognition and Multi-Agent Interaction. From Cognitive Modeling to Social Simulation. Cambridge University Press, Cambridge (2006) 33. : Probably Approximately Correct. Nature’s Algorithms for Learning and Prospering in a Complex World.
IGI Global, Hershey (2008) Innovation and Big Data H. com Abstract. Innovation is an essential issue for companies and educational institutes. We have seen that well-known companies came into trouble since they did not innovate in time. They kept their well-established way of operating and adhered to their old-fashioned business models. The main topic of this contribution is to address the question: to what extent can the availability of Big Data support the innovation attempts of companies and educational institutes?
We then formulate six possible classes of obstacles and take into account the use of sensitive data. Finally, we arrive at two conclusions and three recommendations. Keywords: Big data Á Obstacles management Á Narrative science Á Sensitive data Á Safeguards Á Turn around 1 Introduction The current technological development is in a state of flux. New applications are followed by even newer ones. Many scientists see this concatenation of applications as a disruptive chain. For a proper understanding we mention ﬁve new developments (or applications of well-known concepts): (1) autonomous cars, (2) blockchains, (3) crowd sourced online dispute resolutions, (4) Airbnb, and (5) Uber Taxi.