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Link de la búsquedaAdvances in Data Analysis, Data Handling and Business Intelligence / SpringerLink (Online service) ; Andreas Fink ; Berthold Lausen ; Seidel, Wilfried ; Alfred Ultsch (2010)
Título : Advances in Data Analysis, Data Handling and Business Intelligence : Proceedings of the 32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), Helmut-Schmidt-University, Hamburg, July 16-18, 2008 Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Andreas Fink ; Berthold Lausen ; Seidel, Wilfried ; Alfred Ultsch Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2010 Colección: Studies in Classification, Data Analysis, and Knowledge Organization, ISSN 1431-8814 Número de páginas: XXVI, 695 p. 172 illus., 68 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-642-01044-6 Idioma : Inglés (eng) Palabras clave: Computer science Information technology Business Data processing mining Artificial intelligence Statistics Science Intelligence (incl. Robotics) Statistics, general IT in Mining and Knowledge Discovery Clasificación: 51 Matemáticas Resumen: Data Analysis, Data Handling and Business Intelligence are research areas at the intersection of computer science, artificial intelligence, mathematics, and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as in marketing, finance, economics, engineering, linguistics, archaeology, musicology, medical science, and biology. This volume contains the revised versions of selected papers presented during the 32nd Annual Conference of the German Classification Society (Gesellschaft für Klassifikation, GfKl). The conference, which was organized in cooperation with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), was hosted by Helmut-Schmidt-University, Hamburg, Germany, in July 2008 Nota de contenido: Invited -- Clustering and Classification -- Mixture Analysis -- Linguistics and Text Analysis -- Pattern Recognition and Machine Learning -- Statistical Musicology -- Banking and Finance -- Marketing, Management Science and Economics -- Archaeology and Spatial Planning -- Bio- and Health Sciences -- Exploratory Data Analysis, Modeling and Applications En línea: http://dx.doi.org/10.1007/978-3-642-01044-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33700 Advances in Data Analysis, Data Handling and Business Intelligence : Proceedings of the 32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), Helmut-Schmidt-University, Hamburg, July 16-18, 2008 [documento electrónico] / SpringerLink (Online service) ; Andreas Fink ; Berthold Lausen ; Seidel, Wilfried ; Alfred Ultsch . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2010 . - XXVI, 695 p. 172 illus., 68 illus. in color : online resource. - (Studies in Classification, Data Analysis, and Knowledge Organization, ISSN 1431-8814) .
ISBN : 978-3-642-01044-6
Idioma : Inglés (eng)
Palabras clave: Computer science Information technology Business Data processing mining Artificial intelligence Statistics Science Intelligence (incl. Robotics) Statistics, general IT in Mining and Knowledge Discovery Clasificación: 51 Matemáticas Resumen: Data Analysis, Data Handling and Business Intelligence are research areas at the intersection of computer science, artificial intelligence, mathematics, and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as in marketing, finance, economics, engineering, linguistics, archaeology, musicology, medical science, and biology. This volume contains the revised versions of selected papers presented during the 32nd Annual Conference of the German Classification Society (Gesellschaft für Klassifikation, GfKl). The conference, which was organized in cooperation with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), was hosted by Helmut-Schmidt-University, Hamburg, Germany, in July 2008 Nota de contenido: Invited -- Clustering and Classification -- Mixture Analysis -- Linguistics and Text Analysis -- Pattern Recognition and Machine Learning -- Statistical Musicology -- Banking and Finance -- Marketing, Management Science and Economics -- Archaeology and Spatial Planning -- Bio- and Health Sciences -- Exploratory Data Analysis, Modeling and Applications En línea: http://dx.doi.org/10.1007/978-3-642-01044-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33700 Ejemplares
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Título : Artificial Intelligence in Financial Markets : Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics Tipo de documento: documento electrónico Autores: Christian L. Dunis ; SpringerLink (Online service) ; Peter W. Middleton ; Andreas Karathanasopolous ; Theofilatos, Konstantinos Editorial: London : Palgrave Macmillan UK Fecha de publicación: 2016 Otro editor: Imprint: Palgrave Macmillan Colección: New Developments in Quantitative Trading and Investment Número de páginas: XV, 344 p. 49 illus., 17 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-137-48880-0 Idioma : Inglés (eng) Palabras clave: Finance Corporations Banks and banking Investment Securities Risk management Artificial intelligence Economics, Mathematical Corporate Investments Banking Management Quantitative Intelligence (incl. Robotics) Clasificación: 330 Economía en general Resumen: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field. Nota de contenido: 1. A Review of Applications of Artificial Intelligence in Financial Domain -- SECTION I: Financial Forecasting and Trading -- 2. Trading the FTSE100 Index - 'Adaptive' Modelling and Optimisation Techniques -- 3. Modelling, Forecasting and Trading the Crack - A Sliding Window Approach to Training Neural Networks -- 4. GEPTrader: A new Standalone Tool for Constructing Trading Strategies with Gene Expression Programming -- SECTION II: ECONOMICS -- 5. Business Intelligence for Decision Making in Economics -- 6. An automated literature analysis on data mining applications to credit risk assessment -- SECTION III: CREDIT RISK ANALYSIS -- 7. Intelligent credit risk decision support: architecture and implementations -- 8. Artificial Intelligence for Islamic Sukuk Rating Predictions -- SECTION IV: PORTFOLIO MANAGEMENT, ANALYSIS AND OPTIMISATION -- 9. Portfolio selection as a multiperiod choice problem under uncertainty: an interation-based approach -- 10. Handling model risk in portfolio selection using a Multi-Objective Genetic Algorithm -- 11. Linear regression versus fuzzy linear regression - does it make a difference in the evaluation of the performance of mutual fund managers? En línea: http://dx.doi.org/10.1057/978-1-137-48880-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=41978 Artificial Intelligence in Financial Markets : Cutting Edge Applications for Risk Management, Portfolio Optimization and Economics [documento electrónico] / Christian L. Dunis ; SpringerLink (Online service) ; Peter W. Middleton ; Andreas Karathanasopolous ; Theofilatos, Konstantinos . - London : Palgrave Macmillan UK : Imprint: Palgrave Macmillan, 2016 . - XV, 344 p. 49 illus., 17 illus. in color : online resource. - (New Developments in Quantitative Trading and Investment) .
ISBN : 978-1-137-48880-0
Idioma : Inglés (eng)
Palabras clave: Finance Corporations Banks and banking Investment Securities Risk management Artificial intelligence Economics, Mathematical Corporate Investments Banking Management Quantitative Intelligence (incl. Robotics) Clasificación: 330 Economía en general Resumen: As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field. Nota de contenido: 1. A Review of Applications of Artificial Intelligence in Financial Domain -- SECTION I: Financial Forecasting and Trading -- 2. Trading the FTSE100 Index - 'Adaptive' Modelling and Optimisation Techniques -- 3. Modelling, Forecasting and Trading the Crack - A Sliding Window Approach to Training Neural Networks -- 4. GEPTrader: A new Standalone Tool for Constructing Trading Strategies with Gene Expression Programming -- SECTION II: ECONOMICS -- 5. Business Intelligence for Decision Making in Economics -- 6. An automated literature analysis on data mining applications to credit risk assessment -- SECTION III: CREDIT RISK ANALYSIS -- 7. Intelligent credit risk decision support: architecture and implementations -- 8. Artificial Intelligence for Islamic Sukuk Rating Predictions -- SECTION IV: PORTFOLIO MANAGEMENT, ANALYSIS AND OPTIMISATION -- 9. Portfolio selection as a multiperiod choice problem under uncertainty: an interation-based approach -- 10. Handling model risk in portfolio selection using a Multi-Objective Genetic Algorithm -- 11. Linear regression versus fuzzy linear regression - does it make a difference in the evaluation of the performance of mutual fund managers? En línea: http://dx.doi.org/10.1057/978-1-137-48880-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=41978 Ejemplares
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Título : Business Intelligence : 5th European Summer School, eBISS 2015, Barcelona, Spain, July 5-10, 2015, Tutorial Lectures Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Esteban Zimányi ; Alberto Abelló Editorial: Cham : Springer International Publishing Fecha de publicación: 2016 Otro editor: Imprint: Springer Colección: Lecture Notes in Business Information Processing, ISSN 1865-1348 num. 253 Número de páginas: IX, 131 p. 37 illus Il.: online resource ISBN/ISSN/DL: 978-3-319-39243-1 Idioma : Inglés (eng) Palabras clave: Computer science Big data system failures Data mining Information storage and retrieval Artificial intelligence Application software Science Storage Retrieval Data/Analytics System Performance Evaluation Intelligence (incl. Robotics) Appl. in Administrative Processing Mining Knowledge Discovery Clasificación: 658 Empresas. Organización de empresas Resumen: This book constitutes the tutorial lectures of the 5th European Business Intelligence Summer School, eBISS 2015, held in Barcelona, Spain, in July 2015. The tutorials presented here in an extended and refined format were given by renowned experts and cover topics including schema evolution for databases and data warehouses, publishing OLAP cubes on the Semantic Web, design issues in social business intelligence projects, context-aware business intelligence, and key performance indicators in data warehouses Nota de contenido: Schema Evolution for Databases and Data Warehouses -- Publishing OLAP Cubes on the Semantic Web -- Design Issues in Social Business Intelligence Projects -- Context-Aware Business Intelligence -- Key Performance Indicators in Data Warehouses -- Author Index En línea: http://dx.doi.org/10.1007/978-3-319-39243-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=40996 Business Intelligence : 5th European Summer School, eBISS 2015, Barcelona, Spain, July 5-10, 2015, Tutorial Lectures [documento electrónico] / SpringerLink (Online service) ; Esteban Zimányi ; Alberto Abelló . - Cham : Springer International Publishing : Imprint: Springer, 2016 . - IX, 131 p. 37 illus : online resource. - (Lecture Notes in Business Information Processing, ISSN 1865-1348; 253) .
ISBN : 978-3-319-39243-1
Idioma : Inglés (eng)
Palabras clave: Computer science Big data system failures Data mining Information storage and retrieval Artificial intelligence Application software Science Storage Retrieval Data/Analytics System Performance Evaluation Intelligence (incl. Robotics) Appl. in Administrative Processing Mining Knowledge Discovery Clasificación: 658 Empresas. Organización de empresas Resumen: This book constitutes the tutorial lectures of the 5th European Business Intelligence Summer School, eBISS 2015, held in Barcelona, Spain, in July 2015. The tutorials presented here in an extended and refined format were given by renowned experts and cover topics including schema evolution for databases and data warehouses, publishing OLAP cubes on the Semantic Web, design issues in social business intelligence projects, context-aware business intelligence, and key performance indicators in data warehouses Nota de contenido: Schema Evolution for Databases and Data Warehouses -- Publishing OLAP Cubes on the Semantic Web -- Design Issues in Social Business Intelligence Projects -- Context-Aware Business Intelligence -- Key Performance Indicators in Data Warehouses -- Author Index En línea: http://dx.doi.org/10.1007/978-3-319-39243-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=40996 Ejemplares
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Título : The Nexus between Artificial Intelligence and Economics Tipo de documento: documento electrónico Autores: Ad. J. W. van de Gevel ; SpringerLink (Online service) ; Charles N. Noussair Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2013 Otro editor: Imprint: Springer Colección: SpringerBriefs in Economics, ISSN 2191-5504 Número de páginas: VIII, 115 p. 1 illus Il.: online resource ISBN/ISSN/DL: 978-3-642-33648-5 Idioma : Inglés (eng) Palabras clave: Artificial intelligence Economic theory Behavioral economics Microeconomics Economics Intelligence (incl. Robotics) Behavioral/Experimental Theory/Quantitative Economics/Mathematical Methods Clasificación: 658 Empresas. Organización de empresas Resumen: The manuscript reviews some key ideas about artificial intelligence, and relates them to economics. These include its relation to robotics, and the concepts of synthetic emotions, consciousness, and life. The economic implications of the advent of artificial intelligence, such as its effect on prices and wages, appropriate patent policy, and the possibility of accelerating productivity, are discussed. The growing field of artificial economics and the use of artificial agents in experimental economics is considered Nota de contenido: Introduction -- Technological Progress: Logistic Growth or Singularity -- Artificial Intelligence -- Artificial Happiness -- Issues in Artificial Intelligence -- Artificial Intelligence in Economics: ACE -- Economics of Artificial Intelligence -- State of the Art, Challenges for AGI En línea: http://dx.doi.org/10.1007/978-3-642-33648-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=36551 The Nexus between Artificial Intelligence and Economics [documento electrónico] / Ad. J. W. van de Gevel ; SpringerLink (Online service) ; Charles N. Noussair . - Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013 . - VIII, 115 p. 1 illus : online resource. - (SpringerBriefs in Economics, ISSN 2191-5504) .
ISBN : 978-3-642-33648-5
Idioma : Inglés (eng)
Palabras clave: Artificial intelligence Economic theory Behavioral economics Microeconomics Economics Intelligence (incl. Robotics) Behavioral/Experimental Theory/Quantitative Economics/Mathematical Methods Clasificación: 658 Empresas. Organización de empresas Resumen: The manuscript reviews some key ideas about artificial intelligence, and relates them to economics. These include its relation to robotics, and the concepts of synthetic emotions, consciousness, and life. The economic implications of the advent of artificial intelligence, such as its effect on prices and wages, appropriate patent policy, and the possibility of accelerating productivity, are discussed. The growing field of artificial economics and the use of artificial agents in experimental economics is considered Nota de contenido: Introduction -- Technological Progress: Logistic Growth or Singularity -- Artificial Intelligence -- Artificial Happiness -- Issues in Artificial Intelligence -- Artificial Intelligence in Economics: ACE -- Economics of Artificial Intelligence -- State of the Art, Challenges for AGI En línea: http://dx.doi.org/10.1007/978-3-642-33648-5 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=36551 Ejemplares
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Título : Data Analysis, Machine Learning and Applications : Proceedings of the 31st Annual Conference of the Gesellschaft für Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7–9, 2007 Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Preisach, Christine ; Hans Burkhardt ; Schmidt-Thieme, Lars ; Reinhold Decker Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2008 Colección: Studies in Classification, Data Analysis, and Knowledge Organization, ISSN 1431-8814 Número de páginas: XVI, 719 p Il.: online resource ISBN/ISSN/DL: 978-3-540-78246-9 Idioma : Inglés (eng) Palabras clave: Computer science Information technology Business Data processing mining Artificial intelligence Statistics Science Intelligence (incl. Robotics) Statistics, general IT in Mining and Knowledge Discovery Clasificación: 51 Matemáticas Resumen: Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007 Nota de contenido: Classification -- Clustering -- Multidimensional Data Analysis -- Analysis of Complex Data -- Exploratory Data Analysis and Tools for Data Analysis -- Marketing and Management Science -- Banking and Finance -- Business Intelligence -- Text Mining, Web Mining, and the Semantic Web -- Linguistics -- Data Analysis in Humanities En línea: http://dx.doi.org/10.1007/978-3-540-78246-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34372 Data Analysis, Machine Learning and Applications : Proceedings of the 31st Annual Conference of the Gesellschaft für Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7–9, 2007 [documento electrónico] / SpringerLink (Online service) ; Preisach, Christine ; Hans Burkhardt ; Schmidt-Thieme, Lars ; Reinhold Decker . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2008 . - XVI, 719 p : online resource. - (Studies in Classification, Data Analysis, and Knowledge Organization, ISSN 1431-8814) .
ISBN : 978-3-540-78246-9
Idioma : Inglés (eng)
Palabras clave: Computer science Information technology Business Data processing mining Artificial intelligence Statistics Science Intelligence (incl. Robotics) Statistics, general IT in Mining and Knowledge Discovery Clasificación: 51 Matemáticas Resumen: Data analysis and machine learning are research areas at the intersection of computer science, artificial intelligence, mathematics and statistics. They cover general methods and techniques that can be applied to a vast set of applications such as web and text mining, marketing, medical science, bioinformatics and business intelligence. This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl). The conference was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007 Nota de contenido: Classification -- Clustering -- Multidimensional Data Analysis -- Analysis of Complex Data -- Exploratory Data Analysis and Tools for Data Analysis -- Marketing and Management Science -- Banking and Finance -- Business Intelligence -- Text Mining, Web Mining, and the Semantic Web -- Linguistics -- Data Analysis in Humanities En línea: http://dx.doi.org/10.1007/978-3-540-78246-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34372 Ejemplares
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