Descripción del título
Advances in Business ICT: N...
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
Monografía
monografia Rebiun22462427 https://catalogo.rebiun.org/rebiun/record/Rebiun22462427 cr nn 008mamaa 161102s2017 gw s 00 0 eng d 9783319472089 9783319472072 9783319472096 9783319836805 10.1007/978-3-319-47208-9 doi UMA.RE UYQ bicssc COM004000 bisacsh 006.3 23 Advances in Business ICT: New Ideas from Ongoing Research Recurso electrónico] edited by Tomasz Peech-Pilichowski, Maria Mach-Król, Celina M. Olszak Cham Springer International Publishing 2017 Cham Cham Springer International Publishing Cham Springer International Publishing Imprint: Springer 2017 Cham Cham Springer International Publishing Imprint: Springer VII, 135 p. 63 il VII, 135 p. 63 il Text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Studies in Computational Intelligence 658 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 Engineering Information technology Artificial intelligence Computational Intelligence. IT in Business. Artificial Intelligence. Engineering Information technology Artificial intelligence Computational Intelligence IT in Business Artificial Intelligence Peech-Pilichowski, Tomasz ed. lit Mach-Król, Maria ed. lit Olszak, Celina M ed. lit 3-319-47207-0 Studies in Computational Intelligence 658