04635nam 22006495 450 991025435620332120200702124750.03-319-47208-910.1007/978-3-319-47208-9(CKB)3710000001006445(DE-He213)978-3-319-47208-9(MiAaPQ)EBC6303592(MiAaPQ)EBC5592748(Au-PeEL)EBL5592748(OCoLC)1066199049(PPN)19713761X(EXLCZ)99371000000100644520161102d2017 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierAdvances in Business ICT: New Ideas from Ongoing Research /edited by Tomasz Pełech-Pilichowski, Maria Mach-Król, Celina M. Olszak1st ed. 2017.Cham :Springer International Publishing :Imprint: Springer,2017.1 online resource (VII, 135 p. 63 illus.) Studies in Computational Intelligence,1860-949X ;6583-319-47207-0 Advances in Business ICT: New Ideas from Ongoing Research -- Verification of Temporal Knowledge Bases as an Important Aspect of Knowledge Management Processes in Organization -- The role of simulation performance in software-in-the-loop simulations -- Cognitum Ontorion: Knowledge Representation and Reasoning System -- Overview of Selected Business Process Semantization Techniques -- Selected Approaches Towards Taxonomy of Business Process Anomalies -- Hybrid framework for investment project portfolio selection -- Towards Predicting Stock Price Moves with Aid of Sentiment Analysis of Twitter Social Network Data and Big Data Processing Environment -- On a Property of Phase Correlation and Possibilities to Reduce the Walsh Function System.This book discusses the effective use of modern ICT solutions for business needs, including the efficient use of IT resources, decision support systems, business intelligence, data mining and advanced data processing algorithms, as well as the processing of large datasets (inter alia social networking such as Twitter and Facebook, etc.). The ability to generate, record and process qualitative and quantitative data, including in the area of big data, the Internet of Things (IoT) and cloud computing offers a real prospect of significant improvements for business, as well as the operation of a company within Industry 4.0. The book presents new ideas, approaches, solutions and algorithms in the area of knowledge representation, management and processing, quantitative and qualitative data processing (including sentiment analysis), problems of simulation performance, and the use of advanced signal processing to increase the speed of computation. The solutions presented are also aimed at the effective use of business process modeling and notation (BPMN), business process semantization and investment project portfolio selection. It is a valuable resource for researchers, data analysts, entrepreneurs and IT professionals alike, and the research findings presented make it possible to reduce costs, increase the accuracy of investment, optimize resources and streamline operations and marketing.Studies in Computational Intelligence,1860-949X ;658Computational intelligenceInformation technologyBusiness—Data processingArtificial intelligenceComputational Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/T11014IT in Businesshttps://scigraph.springernature.com/ontologies/product-market-codes/522000Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Computational intelligence.Information technology.Business—Data processing.Artificial intelligence.Computational Intelligence.IT in Business.Artificial Intelligence.658.4038011Pełech-Pilichowski Tomaszedthttp://id.loc.gov/vocabulary/relators/edtMach-Król Mariaedthttp://id.loc.gov/vocabulary/relators/edtOlszak Celina Medthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910254356203321Advances in Business ICT: New Ideas from Ongoing Research2260467UNINA