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Advanced data mining and applications . Part I : 17th international conference, ADMA 2021, Sydney, NSW, Australia, February 2-4, 2022, proceedings / / Bohan Li [and seven others], editors
| Advanced data mining and applications . Part I : 17th international conference, ADMA 2021, Sydney, NSW, Australia, February 2-4, 2022, proceedings / / Bohan Li [and seven others], editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2022] |
| Descrizione fisica | 1 online resource (449 pages) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Data mining
Data mining - Data processing Mineria de dades |
| Soggetto genere / forma |
Congressos
Llibres electrònics |
| ISBN | 3-030-95405-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464538703316 |
| Cham, Switzerland : , : Springer International Publishing, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Digital economy : emerging technologies and business innovation : 6th International Conference on Digital Economy, ICDEc 2021, Tallinn, Estonia, July 15-17, 2021 : proceedings / / Rim Jallouli [and four others]
| Digital economy : emerging technologies and business innovation : 6th International Conference on Digital Economy, ICDEc 2021, Tallinn, Estonia, July 15-17, 2021 : proceedings / / Rim Jallouli [and four others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (297 pages) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Business Information Processing Ser. |
| Soggetto topico |
Data mining - Data processing
Information technology - Technological innovations |
| ISBN | 3-030-92909-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Keynote Talks -- Internet of Things Healthcare System for Reducing Economic Burden -- Resilience in Times of Accelerated Digital Transformation -- Invited Talks -- Creating Seamless Online Experiences to SMEs -- How Estonia Creates E-country E-Estonia. Com: A Toolkit for any Startup Working Remotely -- Round Table -- Mental Manipulations and Neurotechnology: Redefining Neuro- and Cognitive Security -- Contents -- Digital Strategies -- Women in ICT: The Case of Croatia Within European Union -- 1 Introduction -- 2 Literature Review -- 3 Women ICT Specialists in Croatia -- 4 Data and Methodology -- 5 Result and Discussion -- 6 Conclusion -- References -- The Strategic Values of Omnichannel Behavior in the Age of Covid-19 -- 1 Introduction -- 2 Theoretical Framework -- 2.1 COVID-19 -- 2.2 An Emerging Omnichannel Trend -- 2.3 The Value -- 2.4 The Co-creation of Value -- 2.5 The Opportunities for Co-creating Value Offered by the Multiplication of Channels -- 3 Methodology -- 4 Values of Omnichannel Behavior During Covid-19 Pandemic: Key Findings -- 4.1 Informative Value -- 4.2 Social Value -- 4.3 The Value of Convenience -- 4.4 Recreational Value -- 5 Conclusion -- Appendix 1: Characteristics of the sample -- References -- Development of an Intelligent Win-Win Negotiation Model -- 1 Introduction -- 2 Theoretical Background -- 2.1 Negotiation Theoretical Status -- 2.2 Automated Negotiation -- 2.3 Negotiation in Procurement -- 2.4 Artificial Intelligence in Automated Negotiation -- 3 Eliciting the Contribution -- 3.1 The Win-Win Negotiation Process Model -- 3.2 The Adjustment of Utility Measurement in Cooperative Negotiation -- 4 Model Building -- 4.1 Games Theory: Bayes Nash Equilibrium in Incomplete Information -- 4.2 AI: Machine Learning for Predicting Preference Models -- 4.3 From ZOPA to ZOPP.
5 Experiment and Results -- 5.1 Experiment Overview -- 5.2 Experiment Assumptions -- 5.3 Implementation -- 5.4 Results -- 6 Conclusion and Future Work -- References -- Virtual Communities -- The Impact of National Diversity on Task Conflict in Global Virtual Teams: The Moderating Effect of Language Factors -- 1 Introduction -- 2 Conceptual Framework -- 2.1 National Diversity -- 2.2 Task Conflict -- 2.3 English Skills -- 2.4 Openness to Linguistic Diversity -- 2.5 Research Model -- 3 Method -- 3.1 Sample -- 3.2 Measures -- 4 Results -- 5 Conclusion -- References -- Virtual Communities and Wellbeing: A Systematic Literature Review and Recommendations for Future Research -- 1 Introduction -- 1.1 Virtual Communities -- 1.2 Wellbeing -- 2 Related Works Discussing the Relationship Between Virtual Communities and Wellbeing -- 3 Methodology -- 3.1 Keywords Based Search -- 3.2 Content Analysis -- 4 Results and Discussion -- 4.1 Descriptive Analysis -- 4.2 Related Research Fields and Methodologies -- 5 Platform Types, Support Tools and Wellbeing -- 6 Conclusion and Recommendations for Future Research -- Appendix -- References -- Digital Assets and Blockchain Technology -- Blockchain Technology Diffusion and Adoption: Tunisian Context Exploration -- 1 Introduction -- 2 Literature Review -- 2.1 Blockchain Technologies: Overview and Definition -- 2.2 Blockchain Types -- 2.3 Blockchain Technology Characteristics -- 2.4 Blockchain Technology Advantages -- 2.5 Blockchain Technology Applications -- 3 Theoretical Foundations (Rogers' Theory) -- 4 Theoretical Constructs -- 4.1 Blockchain Diffusion Process and Adoption Curve -- 4.2 Adoption Factors of Blockchain Technology -- 5 Research Design -- 6 Research Results -- 6.1 Tunisian Ecosystem of Blockchain Technology -- 6.2 Adoption Decision Process and Adoption Curve in Tunisia -- 6.3 Blockchain Adoption Factors. 6.4 Assumptions Validation and Research Contributions -- 7 Conclusion -- References -- An Assessment of Inter-market Volatility and Shock Dynamics of Bitcoin as a Digital Asset -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Econometric Model -- 3.2 Data Characteristics -- 4 Empirical Results -- 5 Discussion of Results -- 6 Conclusion -- Appendix -- References -- Artificial Intelligence and Data Science -- A Framework for Corporate Artificial Intelligence Strategy -- 1 Introduction -- 2 Background -- 2.1 Artificial Intelligence (AI) -- 2.2 AI Strategy -- 3 Current State of Research -- 3.1 Previous Studies -- 3.2 Research Gap -- 4 Research Approach and Methods -- 4.1 Systematic Literature Review -- 4.2 Development of Conceptual Framework -- 5 Results -- 5.1 Factors and Framework for AI Strategy -- 5.2 Strategic AI Themes -- 6 Conclusion, Limitations, and Future Research Opportunities -- References -- Testing the Applicability of Digital Decision Support on a Nationwide EHR -- 1 Introduction -- 2 The Methods -- 3 Main Findings -- 3.1 Summary of the Applicability of the Algorithms -- 3.2 Limitations of EHIS Data Model -- 3.3 Limitations of the EHIS Event Model -- 3.4 Limitations of the EHIS Integrations -- 4 Discussion -- 5 Conclusions -- References -- Topic Modeling of Marketing Scientific Papers: An Experimental Survey -- 1 Introduction -- 2 Related Works -- 3 Topic Modeling -- 3.1 Latent Semantic Analysis (LSA) -- 3.2 Latent Dirichlet Allocation (LDA) -- 3.3 Correlated Topic Model (CTM) -- 4 Evaluation Methodology of Topic Modeling Techniques -- 4.1 Aim of the Experiments -- 4.2 Data Set -- 4.3 Objective Evaluation -- 4.4 Subjective Evaluation -- 5 Experiments and Discussions -- 5.1 Objective Evaluation -- 5.2 Subjective Evaluation -- 6 Discussion -- 7 Conclusion -- References. Cross-Domain Sentiment Analysis of the Natural Romanian Language -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Findings -- 5 Conclusions -- References -- Online Education -- Transition to Tertiary Education and eLearning in Lebanon Against the Backdrop of Economic Collapse and Covid-19 Pandemic -- 1 Introduction -- 2 Methodology and Data collection -- 3 Results -- 3.1 Students' Satisfaction and Connectivity -- 3.2 The Effects of Covid-19 and eLearning on the Lived Experience of New Students: The Level on Mental Uneasiness -- 3.3 Academic Needs Related to Online Education -- 4 Discussion -- 4.1 Connectivity and Student Satisfaction -- 4.2 The Level on Mental Uneasiness in Time of Covid-19 and Forced Transition to eLearning -- 4.3 Academic Challenges in a Context of Forced Online University -- 5 Conclusion and Recommendations -- References -- Online Education in Lebanon During the Covid-19 Crisis: An Ongoing Coping Phase -- 1 Introduction -- 2 The Global and the National Contexts -- 2.1 Experiences from Different Countries -- 2.2 Lebanese Schools in Numbers -- 2.3 Initial Response of Lebanese Educational System to Covid-19 Lockdown -- 3 Data Collection and Methodology -- 4 Results -- 4.1 Access to Technology -- 4.2 Ability to Use Technology -- 4.3 Ability to Invest Technology Pedagogically -- 5 Discussion -- 6 Conclusion and Recommendations -- References -- Digital Transformation -- Strategic Management for Digital Transformation: pro et contra -- 1 Introduction -- 2 Design of the Study -- 3 Effects of Digital Transformation on Business and Management -- 4 Specifics of Digital Transformation and Strategic Management in Russia -- 5 Required Changes in Strategic Management -- 6 Conclusion -- References -- Digital Servitization as a New Research Stream: A Bibliometric Analysis -- 1 Introduction -- 2 Theoretical Background. 2.1 Servitization in the Scholarly Literature -- 2.2 Digitalization in the Scholarly Literature -- 2.3 The Emergence of Digital Servitization -- 3 Methodology -- 4 Results -- 5 Preliminary Conclusions and Contributions -- References -- Augmented Reality and IOT -- Augmented Reality Humans: Towards Multisensorial Awareness -- 1 Introduction -- 2 Virtual Humans in Augmented Reality: Observations -- 3 Virtual Humans in See-Through Augmented Reality: Examples -- 4 Believability and Presence -- 5 Presence and Virtual Humans -- 6 Multisensorial Awareness of Multimodal Events -- 7 Conclusions -- References -- Collecting Big Data in Cinemas to Improve Recommendation Systems - A Model with Three Types of Motion Sensors -- 1 Introduction -- 2 State of the Art -- 2.1 Recommendation Systems Based on Conscious Choices -- 2.2 Body Movement -- 3 Sensor Analysis and Model Development -- 3.1 Acceptable Sensors for Body Movement Measuring in a Cinema -- 3.2 Model Development -- 3.3 Data Processing and Results -- 4 Discussion and Conclusion -- References -- Pairing Tweets with the Right Location -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach: DigiCities -- 4 Methodology -- 4.1 DigiCities: Creating Digital Profile of Cities -- 4.2 Append Strategy and Replace Strategy -- 4.3 Data, Experimentation, Algorithms and Evaluation -- 5 Findings -- 5.1 Impact of DigiCities (Prior to Preprocessing) -- 5.2 Impact of DigiCities and Preprocessing -- 5.3 Append Strategy Vs. Replace Strategy -- 6 Conclusion, Limitations and Future Work -- References -- Author Index. |
| Record Nr. | UNISA-996464524203316 |
| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Handbook of research on advanced data mining techniques and applications for business intelligence / / Shrawan Kumar Trivedi [and three others]
| Handbook of research on advanced data mining techniques and applications for business intelligence / / Shrawan Kumar Trivedi [and three others] |
| Pubbl/distr/stampa | Hershey, Pennsylvania : , : IGI Global, , 2017 |
| Descrizione fisica | 1 online resource (465 pages) : illustrations |
| Disciplina | 005.74 |
| Collana | Advances in Business Information Systems and Analytics (ABISA) Book Series |
| Soggetto topico | Data mining - Data processing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910164875203321 |
| Hershey, Pennsylvania : , : IGI Global, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Predictive analytics and data mining : concepts and practice with rapidminer / / Vijay Kotu, Bala Deshpande
| Predictive analytics and data mining : concepts and practice with rapidminer / / Vijay Kotu, Bala Deshpande |
| Autore | Kotu Vijay |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Waltham, Massachusetts : , : Elsevier Inc, , 2015 |
| Descrizione fisica | 1 online resource (447 p.) |
| Disciplina | 006.312 |
| Soggetto topico |
Data mining - Data processing
Consumer behavior - Economic aspects |
| Soggetto genere / forma | Electronic books. |
| ISBN |
0-12-801460-1
0-12-801650-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""Front Cover""; ""Predictive Analyticsand Data Mining""; ""Copyright""; ""Dedication""; ""Contents""; ""Foreword""; ""Preface""; ""WHY THIS BOOK?""; ""WHO CAN USE THIS BOOK?""; ""Acknowledgments""; ""Chapter 1 -Introduction""; ""1.1 WHAT DATA MINING IS""; ""1.2 WHAT DATA MINING IS NOT""; ""1.3 THE CASE FOR DATA MINING""; ""1.4 TYPES OF DATA MINING""; ""1.5 DATA MINING ALGORITHMS""; ""1.6 ROADMAP FOR UPCOMING CHAPTERS""; ""REFERENCES""; ""Chapter 2 - Data Mining Process""; ""2.1 PRIOR KNOWLEDGE""; ""2.2 DATA PREPARATION""; ""2.3 MODELING""; ""2.4 APPLICATION""; ""2.5 KNOWLEDGE""
""REFERENCES""""Chapter 6 - Association Analysis""; ""6.1 CONCEPTS OF MINING ASSOCIATION RULES""; ""6.2 Apriori Algorithm""; ""6.3 FP-GROWTH ALGORITHM""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 7 - Clustering""; ""CLUSTERING TO DESCRIBE THE DATA""; ""CLUSTERING FOR PREPROCESSING""; ""7.1 TYPES OF CLUSTERING TECHNIQUES""; ""7.2 K-MEANS CLUSTERING""; ""7.3 DBSCAN CLUSTERING""; ""7.4 SELF-ORGANIZING MAPS""; ""REFERENCES""; ""Chapter 8 - Model Evaluation""; ""8.1 CONFUSION MATRIX (OR TRUTH TABLE)""; ""8.2 RECEIVER OPERATOR CHARACTERISTIC (ROC) CURVES AND AREA UNDER THE CURVE (AUC)"" ""8.3 LIFT CURVES""""8.4 EVALUATING THE PREDICTIONS: IMPLEMENTATION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 9 - Text Mining""; ""9.1 HOW TEXT MINING WORKS""; ""9.2 IMPLEMENTING TEXT MINING WITH CLUSTERING AND CLASSIFICATION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 10 - Time Series Forecasting""; ""10.1 DATA-DRIVEN APPROACHES""; ""10.2 MODEL-DRIVEN FORECASTING METHODS""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 11 - Anomaly Detection""; ""11.1 ANOMALY DETECTION CONCEPTS""; ""11.3 DENSITY-BASED OUTLIER DETECTION""; ""11.4 LOCAL OUTLIER FACTOR""; ""CONCLUSION""; ""REFERENCES"" ""Chapter 12 - Feature Selection""""12.1 CLASSIFYING FEATURE SELECTION METHODS""; ""12.2 PRINCIPAL COMPONENT ANALYSIS""; ""12.3 INFORMATION THEORY�BASED FILTERING FOR NUMERIC DATA""; ""CATEGORICAL DATA""; ""12.5 WRAPPER-TYPE FEATURE SELECTION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 13 - Getting Started with RapidMiner""; ""13.1 USER INTERFACE AND TERMINOLOGY""; ""13.2 DATA IMPORTING AND EXPORTING TOOLS""; ""13.3 DATA VISUALIZATION TOOLS""; ""13.4 DATA TRANSFORMATION TOOLS""; ""13.5 SAMPLING AND MISSING VALUE TOOLS""; ""CONCLUSION""; ""REFERENCES"" ""Comparison of Data Mining Algorithms"" |
| Record Nr. | UNINA-9910463638803321 |
Kotu Vijay
|
||
| Waltham, Massachusetts : , : Elsevier Inc, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Predictive analytics and data mining : concepts and practice with rapidminer / / Vijay Kotu, Bala Deshpande
| Predictive analytics and data mining : concepts and practice with rapidminer / / Vijay Kotu, Bala Deshpande |
| Autore | Kotu Vijay |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Waltham, Massachusetts : , : Elsevier Inc, , 2015 |
| Descrizione fisica | 1 online resource (447 p.) |
| Disciplina | 006.312 |
| Soggetto topico |
Data mining - Data processing
Consumer behavior - Economic aspects |
| ISBN |
0-12-801460-1
0-12-801650-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""Front Cover""; ""Predictive Analyticsand Data Mining""; ""Copyright""; ""Dedication""; ""Contents""; ""Foreword""; ""Preface""; ""WHY THIS BOOK?""; ""WHO CAN USE THIS BOOK?""; ""Acknowledgments""; ""Chapter 1 -Introduction""; ""1.1 WHAT DATA MINING IS""; ""1.2 WHAT DATA MINING IS NOT""; ""1.3 THE CASE FOR DATA MINING""; ""1.4 TYPES OF DATA MINING""; ""1.5 DATA MINING ALGORITHMS""; ""1.6 ROADMAP FOR UPCOMING CHAPTERS""; ""REFERENCES""; ""Chapter 2 - Data Mining Process""; ""2.1 PRIOR KNOWLEDGE""; ""2.2 DATA PREPARATION""; ""2.3 MODELING""; ""2.4 APPLICATION""; ""2.5 KNOWLEDGE""
""REFERENCES""""Chapter 6 - Association Analysis""; ""6.1 CONCEPTS OF MINING ASSOCIATION RULES""; ""6.2 Apriori Algorithm""; ""6.3 FP-GROWTH ALGORITHM""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 7 - Clustering""; ""CLUSTERING TO DESCRIBE THE DATA""; ""CLUSTERING FOR PREPROCESSING""; ""7.1 TYPES OF CLUSTERING TECHNIQUES""; ""7.2 K-MEANS CLUSTERING""; ""7.3 DBSCAN CLUSTERING""; ""7.4 SELF-ORGANIZING MAPS""; ""REFERENCES""; ""Chapter 8 - Model Evaluation""; ""8.1 CONFUSION MATRIX (OR TRUTH TABLE)""; ""8.2 RECEIVER OPERATOR CHARACTERISTIC (ROC) CURVES AND AREA UNDER THE CURVE (AUC)"" ""8.3 LIFT CURVES""""8.4 EVALUATING THE PREDICTIONS: IMPLEMENTATION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 9 - Text Mining""; ""9.1 HOW TEXT MINING WORKS""; ""9.2 IMPLEMENTING TEXT MINING WITH CLUSTERING AND CLASSIFICATION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 10 - Time Series Forecasting""; ""10.1 DATA-DRIVEN APPROACHES""; ""10.2 MODEL-DRIVEN FORECASTING METHODS""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 11 - Anomaly Detection""; ""11.1 ANOMALY DETECTION CONCEPTS""; ""11.3 DENSITY-BASED OUTLIER DETECTION""; ""11.4 LOCAL OUTLIER FACTOR""; ""CONCLUSION""; ""REFERENCES"" ""Chapter 12 - Feature Selection""""12.1 CLASSIFYING FEATURE SELECTION METHODS""; ""12.2 PRINCIPAL COMPONENT ANALYSIS""; ""12.3 INFORMATION THEORY�BASED FILTERING FOR NUMERIC DATA""; ""CATEGORICAL DATA""; ""12.5 WRAPPER-TYPE FEATURE SELECTION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 13 - Getting Started with RapidMiner""; ""13.1 USER INTERFACE AND TERMINOLOGY""; ""13.2 DATA IMPORTING AND EXPORTING TOOLS""; ""13.3 DATA VISUALIZATION TOOLS""; ""13.4 DATA TRANSFORMATION TOOLS""; ""13.5 SAMPLING AND MISSING VALUE TOOLS""; ""CONCLUSION""; ""REFERENCES"" ""Comparison of Data Mining Algorithms"" |
| Record Nr. | UNINA-9910787911803321 |
|
Kotu Vijay
|
||
| Waltham, Massachusetts : , : Elsevier Inc, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Predictive analytics and data mining : concepts and practice with rapidminer / / Vijay Kotu, Bala Deshpande
| Predictive analytics and data mining : concepts and practice with rapidminer / / Vijay Kotu, Bala Deshpande |
| Autore | Kotu Vijay |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Waltham, Massachusetts : , : Elsevier Inc, , 2015 |
| Descrizione fisica | 1 online resource (447 p.) |
| Disciplina | 006.312 |
| Soggetto topico |
Data mining - Data processing
Consumer behavior - Economic aspects |
| ISBN |
0-12-801460-1
0-12-801650-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""Front Cover""; ""Predictive Analyticsand Data Mining""; ""Copyright""; ""Dedication""; ""Contents""; ""Foreword""; ""Preface""; ""WHY THIS BOOK?""; ""WHO CAN USE THIS BOOK?""; ""Acknowledgments""; ""Chapter 1 -Introduction""; ""1.1 WHAT DATA MINING IS""; ""1.2 WHAT DATA MINING IS NOT""; ""1.3 THE CASE FOR DATA MINING""; ""1.4 TYPES OF DATA MINING""; ""1.5 DATA MINING ALGORITHMS""; ""1.6 ROADMAP FOR UPCOMING CHAPTERS""; ""REFERENCES""; ""Chapter 2 - Data Mining Process""; ""2.1 PRIOR KNOWLEDGE""; ""2.2 DATA PREPARATION""; ""2.3 MODELING""; ""2.4 APPLICATION""; ""2.5 KNOWLEDGE""
""REFERENCES""""Chapter 6 - Association Analysis""; ""6.1 CONCEPTS OF MINING ASSOCIATION RULES""; ""6.2 Apriori Algorithm""; ""6.3 FP-GROWTH ALGORITHM""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 7 - Clustering""; ""CLUSTERING TO DESCRIBE THE DATA""; ""CLUSTERING FOR PREPROCESSING""; ""7.1 TYPES OF CLUSTERING TECHNIQUES""; ""7.2 K-MEANS CLUSTERING""; ""7.3 DBSCAN CLUSTERING""; ""7.4 SELF-ORGANIZING MAPS""; ""REFERENCES""; ""Chapter 8 - Model Evaluation""; ""8.1 CONFUSION MATRIX (OR TRUTH TABLE)""; ""8.2 RECEIVER OPERATOR CHARACTERISTIC (ROC) CURVES AND AREA UNDER THE CURVE (AUC)"" ""8.3 LIFT CURVES""""8.4 EVALUATING THE PREDICTIONS: IMPLEMENTATION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 9 - Text Mining""; ""9.1 HOW TEXT MINING WORKS""; ""9.2 IMPLEMENTING TEXT MINING WITH CLUSTERING AND CLASSIFICATION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 10 - Time Series Forecasting""; ""10.1 DATA-DRIVEN APPROACHES""; ""10.2 MODEL-DRIVEN FORECASTING METHODS""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 11 - Anomaly Detection""; ""11.1 ANOMALY DETECTION CONCEPTS""; ""11.3 DENSITY-BASED OUTLIER DETECTION""; ""11.4 LOCAL OUTLIER FACTOR""; ""CONCLUSION""; ""REFERENCES"" ""Chapter 12 - Feature Selection""""12.1 CLASSIFYING FEATURE SELECTION METHODS""; ""12.2 PRINCIPAL COMPONENT ANALYSIS""; ""12.3 INFORMATION THEORY�BASED FILTERING FOR NUMERIC DATA""; ""CATEGORICAL DATA""; ""12.5 WRAPPER-TYPE FEATURE SELECTION""; ""CONCLUSION""; ""REFERENCES""; ""Chapter 13 - Getting Started with RapidMiner""; ""13.1 USER INTERFACE AND TERMINOLOGY""; ""13.2 DATA IMPORTING AND EXPORTING TOOLS""; ""13.3 DATA VISUALIZATION TOOLS""; ""13.4 DATA TRANSFORMATION TOOLS""; ""13.5 SAMPLING AND MISSING VALUE TOOLS""; ""CONCLUSION""; ""REFERENCES"" ""Comparison of Data Mining Algorithms"" |
| Record Nr. | UNINA-9910824261403321 |
|
Kotu Vijay
|
||
| Waltham, Massachusetts : , : Elsevier Inc, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Quantum machine learning : what quantum computing means to data mining / / Peter Wittek
| Quantum machine learning : what quantum computing means to data mining / / Peter Wittek |
| Autore | Wittek Peter |
| Edizione | [First edition] |
| Pubbl/distr/stampa | San Diego, California : , : Academic Press, , 2014 |
| Descrizione fisica | 1 online resource (176 p.) |
| Disciplina | 621.3822 |
| Collana | Elsevier Insights |
| Soggetto topico |
Machine learning - Mathematical models
Data mining - Data processing Quantum theory - Data processing |
| Soggetto genere / forma | Electronic books |
| ISBN | 0-12-801099-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Quantum Machine Learning: What Quantum Computing Meansto Data Mining; Copyright; Contents; Preface; Notations; Part One Fundamental Concepts; Chapter 1: Introduction; 1.1Learning Theory and Data Mining; 1.2.Why Quantum Computers?; 1.3.A Heterogeneous Model; 1.4.An Overview of Quantum Machine Learning Algorithms; 1.5.Quantum-Like Learning on Classical Computers; Chapter 2: Machine Learning; 2.1.Data-Driven Models; 2.2.Feature Space; 2.3.Supervised and Unsupervised Learning; 2.4.Generalization Performance; 2.5.Model Complexity; 2.6.Ensembles
2.7.Data Dependencies and Computational ComplexityChapter 3: Quantum Mechanics; 3.1.States and Superposition; 3.2.Density Matrix Representation and Mixed States; 3.3.Composite Systems and Entanglement; 3.4.Evolution; 3.5.Measurement; 3.6.Uncertainty Relations; 3.7.Tunneling; 3.8.Adiabatic Theorem; 3.9.No-Cloning Theorem; Chapter 4:Quantum Computing; 4.1.Qubits and the Bloch Sphere; 4.2.Quantum Circuits; 4.3.Adiabatic Quantum Computing; 4.4.Quantum Parallelism; 4.5.Grover''s Algorithm; 4.6.Complexity Classes; 4.7.Quantum Information Theory; Part Two Classical Learning Algorithms Chapter 5:Unsupervised Learning5.1.Principal Component Analysis; 5.2.Manifold Embedding; 5.3.K-Means and K-Medians Clustering; 5.4.Hierarchical Clustering; 5.5.Density-Based Clustering; Chapter 6:Pattern Recognition and Neural Networks; 6.1.The Perceptron; 6.2.Hopfield Networks; 6.3.Feedforward Networks; 6.4.Deep Learning; 6.5.Computational Complexity; Chapter 7:Supervised Learning and Support Vector Machines; 7.1.K-Nearest Neighbors; 7.2.Optimal Margin Classifiers; 7.3.Soft Margins; 7.4.Nonlinearity and Kernel Functions; 7.5.Least-Squares Formulation; 7.6.Generalization Performance 7.7.Multiclass Problems7.8.Loss Functions; 7.9.Computational Complexity; Chapter 8:Regression Analysis; 8.1.Linear Least Squares; 8.2.Nonlinear Regression; 8.3.Nonparametric Regression; 8.4.Computational Complexity; Chapter 9:Boosting; 9.1.Weak Classifiers; 9.2.AdaBoost; 9.3.A Family of Convex Boosters; 9.4.Nonconvex Loss Functions; Part Three Quantum Computing and Machine Learning; Chapter 10:Clustering Structure and Quantum Computing; 10.1.Quantum Random Access Memory; 10.2.Calculating Dot Products; 10.3.Quantum Principal Component Analysis; 10.4.Toward Quantum Manifold Embedding 10.5.Quantum K-Means10.6.Quantum K-Medians; 10.7.Quantum Hierarchical Clustering; 10.8.Computational Complexity; Chapter 11:Quantum Pattern Recognition; 11.1.Quantum Associative Memory; 11.2.The Quantum Perceptron; 11.3.Quantum Neural Networks; 11.4.Physical Realizations; 11.4.Computational Complexity; Chapter 12:Quantum Classification; 12.1.Nearest Neighbors; 12.2.Support Vector Machines with Grover''s Search; 12.3.Support Vector Machines with Exponential Speedup; 12.4.Computational Complexity; Chapter 13:Quantum Process Tomography and Regression; 13.1.Channel-State Duality 13.2.Quantum Process Tomography |
| Record Nr. | UNISA-996426328203316 |
|
Wittek Peter
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| San Diego, California : , : Academic Press, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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