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Big data in complex and social networks / / edited by My T. Thai, University of Florida, USA, Weili Wu, University of Texas at Dallas, USA, Hui Xiong, Rutgers, The State University of New Jersey, USA
| Big data in complex and social networks / / edited by My T. Thai, University of Florida, USA, Weili Wu, University of Texas at Dallas, USA, Hui Xiong, Rutgers, The State University of New Jersey, USA |
| Pubbl/distr/stampa | Boca Raton : , : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, , [2017] |
| Descrizione fisica | 1 online resource (253 pages) |
| Disciplina | 005.7 |
| Collana | Chapman & Hall/CRC Big Data Series |
| Soggetto topico |
Big data
Online social networks Webometrics |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-315-39668-8
1-78684-286-6 1-315-39670-X 1-315-39669-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | section I. Social networks and complex networks -- section II. Big data and web intelligence -- section III. Security and privacy issues of social networks -- section IV. Applications. |
| Record Nr. | UNINA-9910155009103321 |
| Boca Raton : , : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, , [2017] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big Data in der Mobilität : Akteure, Geschäftsmodelle und Nutzenpotenziale für die Welt von morgen / / von Nadine Gatzert, Susanne Knorre, Horst Müller-Peters, Fred Wagner, Theresa Jost
| Big Data in der Mobilität : Akteure, Geschäftsmodelle und Nutzenpotenziale für die Welt von morgen / / von Nadine Gatzert, Susanne Knorre, Horst Müller-Peters, Fred Wagner, Theresa Jost |
| Autore | Gatzert Nadine |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Gabler, , 2023 |
| Descrizione fisica | 1 online resource (VII, 199 S. 37 Abb.) |
| Disciplina | 005.7 |
| Soggetto topico |
Big data
Strategic planning Leadership Technological innovations Big Data Business Strategy and Leadership Innovation and Technology Management |
| ISBN | 3-658-40511-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ger |
| Nota di contenuto | Einleitung -- Grundlagen: Mobilitätsmarkt, Mobilitätsdaten und Anspruchsberechtigte von Mobilität -- Big Data in der Mobilität und die Perspektive der Stakeholder: Wer sind die Anspruchsberechtigten und zu welchen Ansprüchen sind sie berechtigt? -- Auswirkungen von Big Data auf den Mobilitätsmarkt -- Nutzen, Risiken und die Bereitschaft zum Datenteilen: Eine quantitative Studie aus Sicht der Verbraucher -- Datenbasierte Geschäftsmodellansätze für Versicherungsunternehmen -- Big Data in der Mobilität: Wie sich die Nutzenpotenziale (für die Welt von morgen) heben lassen. |
| Record Nr. | UNINA-9910684560603321 |
Gatzert Nadine
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| Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Gabler, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big data in energy economics / / Hui Liu [and three others]
| Big data in energy economics / / Hui Liu [and three others] |
| Autore | Liu Hui |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (275 pages) |
| Disciplina | 005.7 |
| Collana | Management for Professionals |
| Soggetto topico | Big data |
| ISBN |
981-16-8964-4
981-16-8965-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743355003321 |
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Liu Hui
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| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big data in the GovTech system / / Victoria N. Ostrovskaya, A. V. Bogoviz, editors
| Big data in the GovTech system / / Victoria N. Ostrovskaya, A. V. Bogoviz, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (199 pages) |
| Disciplina | 005.7 |
| Collana | Studies in Big Data |
| Soggetto topico |
Big data
Internet in public administration |
| ISBN | 3-031-04903-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Big Data In The GovTech System: Scientific Vision and Modern Empirical Experience (Introduction) -- Contents -- GovTech in the Provision of High-Tech Educational Services Based on Big Data -- On the Need and Opportunities for Digitalization of the Educational and Methodological Support of the Educational Process in the Context of Improving Its Quality Indicators -- 1 Introduction -- 2 Materials and Method -- 3 Results -- 4 Conclusion -- References -- Effectiveness of the Education System: Comparative Analysis of the Estimated Data Parameters -- 1 Introduction -- 2 Materials and Methods -- 3 Discussion -- 4 Results -- 5 Conclusion -- References -- Modern Educational Platforms for Distance Training on Lean Production -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- The Use of Digital Technologies in the Implementation of the Meta-Subject Approach as a Trend in the Development of the International Educational Environment -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- Digital Skills Shaping as a Factor of Sustainable Development of Higher Education -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- Digital Technologies in the Teacher's Professional Activities -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- Distance Learning in Higher Education: Technologies of the Moodle Electronic Environment -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- State Regulation of the Economy by Industry Using Big Data in the GovTech -- Improving the Application of Information Technology in the Economy of Service Organizations -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- Development of the Service Sector in a Digital Environment -- 1 Introduction -- 2 Methodology.
3 Results -- 4 Conclusion -- References -- Innovative Banking Services in the Conditions of Digitalization -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Conclusion -- References -- Analysis of the FinTech Segment in the Russian Financial Services Market -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusions -- References -- Spatial and Territorial Factors in the Development of Communal Infrastructure Systems -- 1 Introduction -- 2 Results -- 3 Conclusion -- References -- P2P Lending as a New Model of Digital Bank -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Innovations in Accounting and Analytical Support in the Construction of Automated Integrated Systems -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Conclusion -- References -- Digitalization of the Strategic Management Systems of the Oil and Gas Industry Enterprises -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusions -- References -- Digital Divide and Its Bridging with the Help of GovTech Based on Big Data -- Tendencies and Trends in the Process of Digitalization of Personnel Selection by Heads of Commercial Companies -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- Long-Term Effects of COVID-19: How the Pandemic Highlighted the Global Digital Divide -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Youth, Work and Skills: A Map of the Transformation of the Workforce and Employment -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Adaptation of Students to the Digital Space of the Modern World: Problems of Legal Support in Russia -- 1 Introduction -- 2 Materials and Method -- 3 Results -- 4 Conclusion -- References. Efficiency Assessment of Private Investors' Potential for Public-Private Partnership Projects -- 1 Introduction -- 2 Materials and Method -- 3 Results -- 4 Conclusion -- References -- Assessing the Value of Marine Environmental Projects Using the Scrubbing System -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- Diagnostics of Budgetary Potential of Regions in Order to Implement the Value-Oriented Financial Policy of State -- 1 Introduction -- 2 Methodology -- 3 Results -- 4 Conclusion -- References -- Big Data in the GovTech System: Future Perspectives and New Questions (Conclusion). |
| Record Nr. | UNINA-9910586584203321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big Data Innovations and Applications : 5th International Conference, Innovate-Data 2019, Istanbul, Turkey, August 26–28, 2019, Proceedings / / edited by Muhammad Younas, Irfan Awan, Salima Benbernou
| Big Data Innovations and Applications : 5th International Conference, Innovate-Data 2019, Istanbul, Turkey, August 26–28, 2019, Proceedings / / edited by Muhammad Younas, Irfan Awan, Salima Benbernou |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XII, 217 p. 77 illus., 50 illus. in color.) |
| Disciplina | 005.7 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Big data
Application software Computer system failures Database management Artificial intelligence Big Data Information Systems Applications (incl. Internet) System Performance and Evaluation Database Management Artificial Intelligence |
| ISBN | 3-030-27355-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Advances in Big Data Systems -- Machine Learning and Data Analytics -- Big Data Innovation and Applications -- Security and Risk Analysis. |
| Record Nr. | UNINA-9910349287303321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big Data Integration Theory : Theory and Methods of Database Mappings, Programming Languages, and Semantics / / by Zoran Majkić
| Big Data Integration Theory : Theory and Methods of Database Mappings, Programming Languages, and Semantics / / by Zoran Majkić |
| Autore | Majkić Zoran |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (528 p.) |
| Disciplina | 005.7 |
| Collana | Texts in Computer Science |
| Soggetto topico |
Database management
Computer science Computer science - Mathematics Discrete mathematics Electronic data processing - Management Information technology - Management Database Management Computer Science Logic and Foundations of Programming Discrete Mathematics in Computer Science IT Operations Computer Application in Administrative Data Processing |
| ISBN | 3-319-04156-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction and Technical Preliminaries -- Composition of Schema Mappings: Syntax and Semantics -- Definition of DB Category -- Functorial Semantics for Database Schema Mappings -- Extensions of Relational Codd’s Algebra and DB Category -- Categorial RDB Machines -- Operational Semantics for Database Mappings -- The Properties of DB Category -- Weak Monoidal DB Topos. |
| Record Nr. | UNINA-9910299055603321 |
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Majkić Zoran
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big data intelligence and computing : international conference, DataCom 2022, Denarau Island, Fiji, December 8-10, 2022, proceedings / / edited by Ching-Hsien Hsu [and four others]
| Big data intelligence and computing : international conference, DataCom 2022, Denarau Island, Fiji, December 8-10, 2022, proceedings / / edited by Ching-Hsien Hsu [and four others] |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] |
| Descrizione fisica | 1 online resource (570 pages) |
| Disciplina | 005.7 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Big data |
| ISBN |
9789819922338
9789819922321 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Big Data Algorithm and Systems -- Tiansuan Constellation -- 1 Introduction -- 2 Related Work -- 2.1 Design Overview -- 2.2 Edge Computing and AI in Space -- 3 Method -- 3.1 Datasets -- 3.2 Model Design -- 3.3 Hardware -- 4 Experimental Results -- 4.1 The Comparison -- 4.2 Future Work -- 5 Conclusion -- References -- Adopting a Deep Learning Split-Protocol Based Predictive Maintenance Management System for Industrial Manufacturing Operations -- 1 Introduction -- 2 Literature Reviews -- 3 Overview of Predictive Maintenance and Industries 4.0 -- 4 Strategy to Adopt in Predictive Maintenance -- 4.1 Application of Machine Learning Methods to Predict Predictive Maintenance (PdM) -- 5 Pillars of the Total Predictive Maintenance in Industries 4.0 -- 6 Quantum Computing and Digital Manufacturing 4.0 -- 7 Reliability-Centered Maintenance (RCM) -- 7.1 Benefits of the RCM Approach -- 7.2 Key Principles of Reliability-Centered Maintenance (RCM) -- 8 Intelligent Asset Management (IAM and RCM-Controlled Predictive Maintenance) -- 8.1 Wings Within the IAM -- 8.2 Benefits that Could Be Achieved from AIN -- 9 System Architectures and PDM in Industries 4.0 -- 10 AI-Enabled Split-Migration Architecture -- 11 Implementation Details -- 12 Conclusion -- References -- A Digital Twin for Bus Operation in Public Urban Transportation Systems -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Simulation of Urban Mobility (SUMO) -- 3.2 Configuring SUMO to Reproduce Observed Traffic -- 3.3 Bus Operation Digital Twin (BODIT) -- 4 Experiments -- 4.1 Description of the Scenario -- 4.2 Experimental Setup -- 5 Results -- 6 Conclusion and Future Work -- References -- Predicting Residential Property Valuation in Major Towns and Cities on Mainland Fiji -- 1 Introduction -- 2 Literature Review.
2.1 Property Valuation Approaches -- 2.2 Feature Selection of Properties -- 2.3 Machine Learning Models for Property Predictions -- 3 Methodology -- 3.1 Data Analysis -- 3.2 Data Pre-processing -- 3.3 Data Visualization -- 4 Results and Discussion -- 4.1 Evaluation on Test Data -- 5 Conclusion -- 6 Limitations -- 7 Future Work -- References -- Designing an AI-Driven Talent Intelligence Solution: Exploring Big Data to Extend the TOE Framework -- 1 Introduction -- 2 Background of the Study -- 2.1 Ethical Implications of AI in Talent Management -- 2.2 The Application of AI in Talent Management -- 2.3 Career Services in Higher Education -- 2.4 Theories in Technological Adoption -- 3 Design Science Methodology -- 4 Proposed AI Oriented TM Approach -- 5 Discussion and Conclusion -- References -- Development of Bilingual Chatbot for University Related FAQs Using Natural Language Processing and Deep Learning -- 1 Introduction -- 2 Background -- 2.1 What is a Chatbot and How it Works? -- 3 Methodology -- 3.1 Existing Studies -- 4 Proposed Chatbot -- 4.1 NLP Techniques Used -- 4.2 Chatbot Application Development on Web -- 5 Advantages of the Proposed System -- 5.1 24/7 Availability -- 5.2 Instant Response -- 5.3 Consistency -- 5.4 Bilingual -- 6 Chatbot Testing -- 7 Limitations -- 8 Recommendations and Future Scope -- 9 Conclusion -- References -- Machine Learning Algorithms Performance Investigation in Fake News Detection -- 1 Introduction -- 2 Traditional Media -- 2.1 Printed Media -- 2.2 Radio -- 2.3 Television -- 3 Modern Media -- 4 Research Objective -- 5 Methodology -- 6 Literature Review -- 6.1 Naïve Bayes -- 6.2 Decision Tree -- 6.3 Random Forest -- 6.4 Support Vector Machine (SVM) -- 6.5 K-Nearest Neighbors (KNN) -- 6.6 Logistic Regression -- 7 Findings -- 7.1 Algorithm Category Best Suited for Fake News Detection. 7.2 Top 6 Algorithms for Fake News Detection In Recent Five Years -- 7.3 Best Algorithm Performer for Fake News Detection -- 7.4 Naïve Bayes -- 7.5 Decision Tree -- 7.6 Random Forest -- 7.7 Support Vector Machine (SVM) -- 7.8 K-Nearest Neighbor(KNN) -- 7.9 Logistic Regression -- 7.10 Experimental Results Summary -- 8 Discussion -- 9 Conclusion -- 10 Future Work -- References -- Big Data Privacy and Security -- Robust Graph Embedding Recommendation Against Data Poisoning Attack -- 1 Introduction -- 2 Related Work -- 2.1 Graph Graph-Data Attack Methods -- 2.2 Graph-Data Defend Methods -- 3 Preliminaries -- 4 Our Methods -- 4.1 Pre-process GNN Supervised Detection Structure -- 4.2 Pre-process GNN Supervised Detection Method -- 4.3 Optimization of the Model -- 4.4 Model Evaluation Metric -- 5 Experiments -- 5.1 Data-Sets -- 5.2 Baseline Model -- 5.3 Experiment Analysis -- 5.4 Parameter Analysis -- 6 Conclusion -- References -- A Secure Sharing Framework Based on Cloud-Chain Fusion for SWIM -- 1 Introduction -- 2 Data Sharing Analysis -- 2.1 ATM Data and Its Classification -- 2.2 Features of ATM Data Sharing -- 2.3 ATM Data Sharing Trends -- 2.4 Security Requirements of ATM Data Sharing -- 3 Preliminary Knowledge -- 3.1 Cloud Storage -- 3.2 Blockchain -- 3.3 Feasibility of Cloud-Chain Chain Fusion Architecture -- 3.4 Ciphertext Policy Attribute Based Encryption (CPABE) -- 4 The ATM Information Security Framework Based on Cloud-Chain Fusion -- 4.1 ATM Data Sharing Framework -- 4.2 Data Publishing and Discovery Mechanism (DPAD) -- 4.3 Operation Record and Traceability Mechanism -- 4.4 Data Security Protection Mechanism -- 5 Function and Security Analysis -- 6 Future Research Directions -- 6.1 Entities' Attributes Mining and Attribute-Authority Relation Mining Based on Deep Learning. 6.2 The Decentralized CPABE Method for Access Control Based on Homomorphic Encryption and Blockchain -- 6.3 The Data Privacy Protection Based on Computation Offloading and Secure Multi-party Computation -- 7 Conclusion -- References -- Privacy-Protective Distributed Machine Learning Between Rich Devices and Edge Servers Using Confidence Level -- 1 Introduction -- 2 Related Work -- 3 Research Issues and the Proposed Method -- 3.1 Research Issues -- 3.2 Proposed Method -- 4 Implementation and Evaluation of Proposed Model -- 4.1 Dataset -- 4.2 Experimental Environment -- 4.3 Preliminary Experiments -- 4.4 Experiment 1 (Used only Personal Data for Training on Edge Device) -- 4.5 Experiment 2 (Adding Four Individuals Different from the Edge Server) -- 4.6 Consideration About the Amount of Training and Data -- 5 Summary and Future Work -- References -- A Novel Approach of Securing Medical Cyber Physical Systems (MCPS) from DDoS Attacks -- 1 Introduction -- 2 Related Work -- 3 System Model -- 4 Proposed Methodology -- 5 Results and Discussion -- 6 Conclusion -- References -- LTCS: Lightweight Tree-Chain Scheme for ADS-B Data Authentication -- 1 Introduction -- 2 Related Works -- 3 Our Proposed Scheme -- 4 Performance Analysis -- 5 Conclusion -- References -- Electronic and Remote Voting Systems: Solutions to Existing Problems - An Experimental Approach to Secure Voting Platforms on Endpoints -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Why Do We Need to Secure Content Delivery Systems for Voting? -- 3.2 Is Multifactor Authentication not a Viable Option to Secure Platform Delivery? -- 3.3 Do Antivirus Web Browsers Provide Protection for Voting? -- 3.4 Are TLS, SSL, and HTTPS Are not Viable Options for Voting Platforms? -- 4 Experiment -- 4.1 Test Case Theories. 4.2 Test Case 1 - Configuration and Use of Antivirus Solutions for Protected Browser Mode -- 4.3 Test Case 2 - Using the Safe Exam Browser -- 5 Challenges Faced -- 6 Future Works and Recommendations -- 7 Conclusion -- References -- Research on the Mechanism of Cooperative Defense Against DDoS Attacks Based on Game Theory -- 1 Introduction -- 1.1 A Subsection Sample -- 2 Analysis of Research Status and Development Trends -- 2.1 Problems (Defect Analysis) -- 2.2 Analysis of Development Trend -- 3 Defense Against DDoS Attacks Based on Game Theory -- 3.1 Overall Design Idea -- 3.2 Collaborative Defense Scheme -- 3.3 SDN-Based Victim Side Defense Against DDoS Attacks -- 4 Conclusion -- References -- Detection of Malicious Node in VANETs Using Digital Twin -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Phase 1 -- 3.2 Phase 2 -- 4 Results and Discussion -- 5 Conclusion -- References -- Big Data Analytics and Applications -- The Storage and Sharing of Big Data in Air Traffic Management System -- 1 Introduction -- 2 The Architecture of Storage and Sharing for Aviation Big Data -- 2.1 New Aviation Network Architecture -- 2.2 Design of Policy Layer in New Aviation Network -- 2.3 Design of Policy Layer in New Aviation Network -- 3 Application Analysis of New Network Structure -- 4 Conclusion -- References -- Automated Recognition and Classification of Cat Pain Through Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Data Collection -- 3.1 Data Collection -- 4 Model Training -- 4.1 Basic Model Training -- 4.2 Enhanced Model Training -- 5 Conclusions and Future Work -- References -- Perceiving Airline Passenger Booking Lifecycle with the Utilization of Data Warehouse -- 1 Introduction -- 2 Research Methodology -- 3 Related Work -- 3.1 Data Warehouse Implementations -- 3.2 Airline Usecases -- 4 Challenges Whilst Implementing. 5 Benefits of Data Warehouses. |
| Record Nr. | UNISA-996525670503316 |
| Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Big data intelligence and computing : international conference, DataCom 2022, Denarau Island, Fiji, December 8-10, 2022, proceedings / / edited by Ching-Hsien Hsu [and four others]
| Big data intelligence and computing : international conference, DataCom 2022, Denarau Island, Fiji, December 8-10, 2022, proceedings / / edited by Ching-Hsien Hsu [and four others] |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] |
| Descrizione fisica | 1 online resource (570 pages) |
| Disciplina | 005.7 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Artificial intelligence
Big data |
| ISBN |
9789819922338
9789819922321 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Big Data Algorithm and Systems -- Tiansuan Constellation -- 1 Introduction -- 2 Related Work -- 2.1 Design Overview -- 2.2 Edge Computing and AI in Space -- 3 Method -- 3.1 Datasets -- 3.2 Model Design -- 3.3 Hardware -- 4 Experimental Results -- 4.1 The Comparison -- 4.2 Future Work -- 5 Conclusion -- References -- Adopting a Deep Learning Split-Protocol Based Predictive Maintenance Management System for Industrial Manufacturing Operations -- 1 Introduction -- 2 Literature Reviews -- 3 Overview of Predictive Maintenance and Industries 4.0 -- 4 Strategy to Adopt in Predictive Maintenance -- 4.1 Application of Machine Learning Methods to Predict Predictive Maintenance (PdM) -- 5 Pillars of the Total Predictive Maintenance in Industries 4.0 -- 6 Quantum Computing and Digital Manufacturing 4.0 -- 7 Reliability-Centered Maintenance (RCM) -- 7.1 Benefits of the RCM Approach -- 7.2 Key Principles of Reliability-Centered Maintenance (RCM) -- 8 Intelligent Asset Management (IAM and RCM-Controlled Predictive Maintenance) -- 8.1 Wings Within the IAM -- 8.2 Benefits that Could Be Achieved from AIN -- 9 System Architectures and PDM in Industries 4.0 -- 10 AI-Enabled Split-Migration Architecture -- 11 Implementation Details -- 12 Conclusion -- References -- A Digital Twin for Bus Operation in Public Urban Transportation Systems -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Simulation of Urban Mobility (SUMO) -- 3.2 Configuring SUMO to Reproduce Observed Traffic -- 3.3 Bus Operation Digital Twin (BODIT) -- 4 Experiments -- 4.1 Description of the Scenario -- 4.2 Experimental Setup -- 5 Results -- 6 Conclusion and Future Work -- References -- Predicting Residential Property Valuation in Major Towns and Cities on Mainland Fiji -- 1 Introduction -- 2 Literature Review.
2.1 Property Valuation Approaches -- 2.2 Feature Selection of Properties -- 2.3 Machine Learning Models for Property Predictions -- 3 Methodology -- 3.1 Data Analysis -- 3.2 Data Pre-processing -- 3.3 Data Visualization -- 4 Results and Discussion -- 4.1 Evaluation on Test Data -- 5 Conclusion -- 6 Limitations -- 7 Future Work -- References -- Designing an AI-Driven Talent Intelligence Solution: Exploring Big Data to Extend the TOE Framework -- 1 Introduction -- 2 Background of the Study -- 2.1 Ethical Implications of AI in Talent Management -- 2.2 The Application of AI in Talent Management -- 2.3 Career Services in Higher Education -- 2.4 Theories in Technological Adoption -- 3 Design Science Methodology -- 4 Proposed AI Oriented TM Approach -- 5 Discussion and Conclusion -- References -- Development of Bilingual Chatbot for University Related FAQs Using Natural Language Processing and Deep Learning -- 1 Introduction -- 2 Background -- 2.1 What is a Chatbot and How it Works? -- 3 Methodology -- 3.1 Existing Studies -- 4 Proposed Chatbot -- 4.1 NLP Techniques Used -- 4.2 Chatbot Application Development on Web -- 5 Advantages of the Proposed System -- 5.1 24/7 Availability -- 5.2 Instant Response -- 5.3 Consistency -- 5.4 Bilingual -- 6 Chatbot Testing -- 7 Limitations -- 8 Recommendations and Future Scope -- 9 Conclusion -- References -- Machine Learning Algorithms Performance Investigation in Fake News Detection -- 1 Introduction -- 2 Traditional Media -- 2.1 Printed Media -- 2.2 Radio -- 2.3 Television -- 3 Modern Media -- 4 Research Objective -- 5 Methodology -- 6 Literature Review -- 6.1 Naïve Bayes -- 6.2 Decision Tree -- 6.3 Random Forest -- 6.4 Support Vector Machine (SVM) -- 6.5 K-Nearest Neighbors (KNN) -- 6.6 Logistic Regression -- 7 Findings -- 7.1 Algorithm Category Best Suited for Fake News Detection. 7.2 Top 6 Algorithms for Fake News Detection In Recent Five Years -- 7.3 Best Algorithm Performer for Fake News Detection -- 7.4 Naïve Bayes -- 7.5 Decision Tree -- 7.6 Random Forest -- 7.7 Support Vector Machine (SVM) -- 7.8 K-Nearest Neighbor(KNN) -- 7.9 Logistic Regression -- 7.10 Experimental Results Summary -- 8 Discussion -- 9 Conclusion -- 10 Future Work -- References -- Big Data Privacy and Security -- Robust Graph Embedding Recommendation Against Data Poisoning Attack -- 1 Introduction -- 2 Related Work -- 2.1 Graph Graph-Data Attack Methods -- 2.2 Graph-Data Defend Methods -- 3 Preliminaries -- 4 Our Methods -- 4.1 Pre-process GNN Supervised Detection Structure -- 4.2 Pre-process GNN Supervised Detection Method -- 4.3 Optimization of the Model -- 4.4 Model Evaluation Metric -- 5 Experiments -- 5.1 Data-Sets -- 5.2 Baseline Model -- 5.3 Experiment Analysis -- 5.4 Parameter Analysis -- 6 Conclusion -- References -- A Secure Sharing Framework Based on Cloud-Chain Fusion for SWIM -- 1 Introduction -- 2 Data Sharing Analysis -- 2.1 ATM Data and Its Classification -- 2.2 Features of ATM Data Sharing -- 2.3 ATM Data Sharing Trends -- 2.4 Security Requirements of ATM Data Sharing -- 3 Preliminary Knowledge -- 3.1 Cloud Storage -- 3.2 Blockchain -- 3.3 Feasibility of Cloud-Chain Chain Fusion Architecture -- 3.4 Ciphertext Policy Attribute Based Encryption (CPABE) -- 4 The ATM Information Security Framework Based on Cloud-Chain Fusion -- 4.1 ATM Data Sharing Framework -- 4.2 Data Publishing and Discovery Mechanism (DPAD) -- 4.3 Operation Record and Traceability Mechanism -- 4.4 Data Security Protection Mechanism -- 5 Function and Security Analysis -- 6 Future Research Directions -- 6.1 Entities' Attributes Mining and Attribute-Authority Relation Mining Based on Deep Learning. 6.2 The Decentralized CPABE Method for Access Control Based on Homomorphic Encryption and Blockchain -- 6.3 The Data Privacy Protection Based on Computation Offloading and Secure Multi-party Computation -- 7 Conclusion -- References -- Privacy-Protective Distributed Machine Learning Between Rich Devices and Edge Servers Using Confidence Level -- 1 Introduction -- 2 Related Work -- 3 Research Issues and the Proposed Method -- 3.1 Research Issues -- 3.2 Proposed Method -- 4 Implementation and Evaluation of Proposed Model -- 4.1 Dataset -- 4.2 Experimental Environment -- 4.3 Preliminary Experiments -- 4.4 Experiment 1 (Used only Personal Data for Training on Edge Device) -- 4.5 Experiment 2 (Adding Four Individuals Different from the Edge Server) -- 4.6 Consideration About the Amount of Training and Data -- 5 Summary and Future Work -- References -- A Novel Approach of Securing Medical Cyber Physical Systems (MCPS) from DDoS Attacks -- 1 Introduction -- 2 Related Work -- 3 System Model -- 4 Proposed Methodology -- 5 Results and Discussion -- 6 Conclusion -- References -- LTCS: Lightweight Tree-Chain Scheme for ADS-B Data Authentication -- 1 Introduction -- 2 Related Works -- 3 Our Proposed Scheme -- 4 Performance Analysis -- 5 Conclusion -- References -- Electronic and Remote Voting Systems: Solutions to Existing Problems - An Experimental Approach to Secure Voting Platforms on Endpoints -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Why Do We Need to Secure Content Delivery Systems for Voting? -- 3.2 Is Multifactor Authentication not a Viable Option to Secure Platform Delivery? -- 3.3 Do Antivirus Web Browsers Provide Protection for Voting? -- 3.4 Are TLS, SSL, and HTTPS Are not Viable Options for Voting Platforms? -- 4 Experiment -- 4.1 Test Case Theories. 4.2 Test Case 1 - Configuration and Use of Antivirus Solutions for Protected Browser Mode -- 4.3 Test Case 2 - Using the Safe Exam Browser -- 5 Challenges Faced -- 6 Future Works and Recommendations -- 7 Conclusion -- References -- Research on the Mechanism of Cooperative Defense Against DDoS Attacks Based on Game Theory -- 1 Introduction -- 1.1 A Subsection Sample -- 2 Analysis of Research Status and Development Trends -- 2.1 Problems (Defect Analysis) -- 2.2 Analysis of Development Trend -- 3 Defense Against DDoS Attacks Based on Game Theory -- 3.1 Overall Design Idea -- 3.2 Collaborative Defense Scheme -- 3.3 SDN-Based Victim Side Defense Against DDoS Attacks -- 4 Conclusion -- References -- Detection of Malicious Node in VANETs Using Digital Twin -- 1 Introduction -- 2 Literature Review -- 3 Proposed Methodology -- 3.1 Phase 1 -- 3.2 Phase 2 -- 4 Results and Discussion -- 5 Conclusion -- References -- Big Data Analytics and Applications -- The Storage and Sharing of Big Data in Air Traffic Management System -- 1 Introduction -- 2 The Architecture of Storage and Sharing for Aviation Big Data -- 2.1 New Aviation Network Architecture -- 2.2 Design of Policy Layer in New Aviation Network -- 2.3 Design of Policy Layer in New Aviation Network -- 3 Application Analysis of New Network Structure -- 4 Conclusion -- References -- Automated Recognition and Classification of Cat Pain Through Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Data Collection -- 3.1 Data Collection -- 4 Model Training -- 4.1 Basic Model Training -- 4.2 Enhanced Model Training -- 5 Conclusions and Future Work -- References -- Perceiving Airline Passenger Booking Lifecycle with the Utilization of Data Warehouse -- 1 Introduction -- 2 Research Methodology -- 3 Related Work -- 3.1 Data Warehouse Implementations -- 3.2 Airline Usecases -- 4 Challenges Whilst Implementing. 5 Benefits of Data Warehouses. |
| Record Nr. | UNINA-9910720063803321 |
| Singapore : , : Springer Nature Singapore Pte Ltd., , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Big Data Made Easy [[electronic resource] ] : A Working Guide to the Complete Hadoop Toolset / / by Michael Frampton
| Big Data Made Easy [[electronic resource] ] : A Working Guide to the Complete Hadoop Toolset / / by Michael Frampton |
| Autore | Frampton Mike |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Berkeley, CA : , : Apress : , : Imprint : Apress, , 2015 |
| Descrizione fisica | 1 online resource (381 p.) |
| Disciplina |
004
005.7 005.74 |
| Collana | The expert's voice in big data |
| Soggetto topico |
Big data
Database management Computers Big Data Database Management Information Systems and Communication Service |
| ISBN | 1-4842-0094-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""Contents at a Glance""; ""Contents""; ""About the Author""; ""About the Technical Reviewer""; ""Acknowledgments""; ""Introduction""; ""Chapter 1: The Problem with Data""; ""A Definition of “Big Data�""; ""The Potentials and Difficulties of Big Data""; ""Requirements for a Big Data System""; ""How Hadoop Tools Can Help""; ""My Approach""; ""Overview of the Big Data System""; ""Big Data Flow and Storage""; ""Benefits of Big Data Systems""; ""What�s in This Book""; ""Storage: Chapter 2""; ""Data Collection: Chapter 3""; ""Processing: Chapter 4""; ""Scheduling: Chapter 5""
""Data Movement: Chapter 6""""Monitoring: Chapter 7""; ""Cluster Management: Chapter 8""; ""Analysis: Chapter 9""; ""ETL: Chapter 10""; ""Reports: Chapter 11""; ""Summary""; ""Chapter 2: Storing and Configuring Data with Hadoop, YARN, and ZooKeeper""; ""An Overview of Hadoop""; ""The Hadoop V1 Architecture""; ""The Differences in Hadoop V2""; ""The Hadoop Stack""; ""Environment Management""; ""Hadoop V1 Installation""; ""Hadoop 1.2.1 Single-Node Installation""; ""1. Set up Bash shell file for hadoop HOME/.bashrc""; ""2. Set up conf/hadoop-env. sh""; ""3. Create Hadoop temporary directory"" ""4. Set up conf/core-site. xml""""5. Set up conf/mapred-site. xml""; ""6. Set up file conf/hdfs-site. xml""; ""7. Format the file system""; ""Setting up the Cluster""; ""Running a Map Reduce Job Check""; ""Hadoop User Interfaces""; ""Hadoop V2 Installation""; ""ZooKeeper Installation""; ""Manually Accessing the ZooKeeper Servers""; ""The ZooKeeper Client""; ""Hadoop MRv2 and YARN""; ""Running Another Map Reduce Job Test""; ""Hadoop Commands""; ""Hadoop Shell Commands""; ""Hadoop User Commands""; ""Hadoop Administration Commands""; ""Summary"" ""Chapter 3: Collecting Data with Nutch and Solr""""The Environment""; ""Stopping the Servers""; ""Changing the Environment Scripts""; ""Starting the Servers""; ""Architecture 1: Nutch 1.x""; ""Nutch Installation""; ""Solr Installation""; ""Running Nutch with Hadoop 1.8""; ""Architecture 2: Nutch 2.x""; ""Nutch and Solr Configuration""; ""HBase Installation""; ""Gora Configuration""; ""Running the Nutch Crawl""; ""Potential Errors""; ""A Brief Comparison""; ""Summary""; ""Chapter 4: Processing Data with Map Reduce""; ""An Overview of the Word-Count Algorithm""; ""Map Reduce Native"" ""Java Word-Count Example 1""""Describing the Example 1 Code""; ""Running the Example 1 Code""; ""Java Word-Count Example 2""; ""Describing the Example 2 Code""; ""Running the Example 2 Code""; ""Comparing the Examples""; ""Map Reduce with Pig""; ""Installing Pig""; ""Running Pig""; ""Pig User-Defined Functions""; ""Map Reduce with Hive""; ""Installing Hive""; ""Hive Word-Count Example""; ""Map Reduce with Perl""; ""Summary""; ""Chapter 5: Scheduling and Workflow""; ""An Overview of Scheduling""; ""The Capacity Scheduler""; ""The Fair Scheduler""; ""Scheduling in Hadoop V1"" ""V1 Capacity Scheduler"" |
| Record Nr. | UNINA-9910300655503321 |
|
Frampton Mike
|
||
| Berkeley, CA : , : Apress : , : Imprint : Apress, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Big data management : data governance principles for big data analytics / / Peter Ghavami
| Big data management : data governance principles for big data analytics / / Peter Ghavami |
| Autore | Ghavami Peter K. |
| Pubbl/distr/stampa | Berlin ; ; Boston : , : De Gruyter, , [2021] |
| Descrizione fisica | 1 online resource (xviii, 155 pages) |
| Disciplina | 005.7 |
| Soggetto topico | Big data |
| Soggetto non controllato |
Analytics
Big data Data governance Data lifecycle Data management Hadoop |
| ISBN | 3-11-066406-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Frontmatter -- Acknowledgments -- About the Author -- Contents -- Introduction -- Part 1: Big Data Overview -- Chapter 1 Introduction to Big Data -- Chapter 2 Enterprise Data Governance Directive -- Part 2: Big Data Governance Fundamentals -- Chapter 3 Data Risk Management -- Chapter 4 NoSQL Storage and Security Considerations -- Chapter 5 The Key Components of Big Data Governance -- Chapter 6 Big Data Governance Framework -- Chapter 7 Master Data Management -- Chapter 8 Big Data Governance Rules: Best Practices -- Chapter 9 Big Data Governance Best Practices -- Chapter 10 Big Data Governance Framework Program -- Part 3: Big Data and Model Risk Management -- Chapter 11 Why Data and Model Risk Management? -- Summary -- Index |
| Record Nr. | UNINA-9910554279503321 |
|
Ghavami Peter K.
|
||
| Berlin ; ; Boston : , : De Gruyter, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
