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Data science in the library : tools and strategies for supporting data-driven research and instruction / / edited by Joel Herndon
| Data science in the library : tools and strategies for supporting data-driven research and instruction / / edited by Joel Herndon |
| Pubbl/distr/stampa | London : , : Facet Publishing, , 2022 |
| Descrizione fisica | 1 online resource (xxx, 146 pages) |
| Disciplina | 005.74 |
| Soggetto topico |
Database management in libraries
Data curation in libraries Data services librarians Research - Data processing Big data |
| ISBN |
1-78330-518-5
1-78330-461-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ; Introduction: The rise of data science -- ; PART 1: DATA SCIENCE AND RESEARCH LIBRARIES: PERSPECTIVES -- ; 1. Sustainability and success models for informal data science training within libraries / Elizabeth Wickes -- ; 2. The Fundación Juan March DataLab: a data science unit within a research support library / Luis Martínez-Uribe, Paz Fernández and Fernando Martínez-- ; PART 2: DATA SCIENCE INSTRUCTION -- ; 3. Toward reproducibility: academic libraries and open science / Joshua Quan -- ; 4. Start with data science / Mine Çetinkaya-Rundel -- ; PART 3: DATA SCIENCE SERVICES -- ; 5. In support of data-intensive science at the University of Washington / Jenny Muilenburg -- ; 6. From a data archive to data science: supporting current research / Tim Dennis, Zhiyuan Yao, Leigh Phan, et al -- ; PART 4: DESIGNING AND STAFFING DATA SCIENCE -- ; 7. In-house training as the first step to becoming a data savvy librarian / Jeannette Ekstrøm -- ; 8. Designing for data science: planning for library data services / Joel Herndon. |
| Record Nr. | UNINA-9910810043103321 |
| London : , : Facet Publishing, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Discovery science : 25th international conference, DS 2022, Montpellier, France, October 10-12, 2022, proceedings / / edited by Poncelet Pascal and Dino Ienco
| Discovery science : 25th international conference, DS 2022, Montpellier, France, October 10-12, 2022, proceedings / / edited by Poncelet Pascal and Dino Ienco |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (576 pages) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Discoveries in science
Research - Data processing |
| ISBN | 3-031-18840-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Keynote Talks -- Unsupervised Model Selection in Outlier Detection: The Elephant in the Room -- Coloring Social Relationships -- 35 Years of 'Scientific Discovery: Computational Explorations of the Creative Processes' - From the Early Days to the State of the Art -- Contents -- Regression and Limited Data -- Model Optimization in Imbalanced Regression -- 1 Introduction -- 2 Related Work -- 3 Imbalanced Regression -- 3.1 Relevance Function -- 3.2 Squared Error Relevance Area (SERA) -- 4 Optimization Loss Function for Imbalanced Regression -- 5 Experimental Study -- 5.1 Experimental Setup -- 5.2 Results on Model Optimization -- 5.3 Results in Out-of-Sample -- 6 Conclusions -- A SERA numerical approximation -- B Tables of Results -- References -- Discovery of Differential Equations Using Probabilistic Grammars -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Algebraic Equations and Numeric Differentiation -- 3.2 Differential Equations and Direct Simulation -- 3.3 Parallel Computation -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Hyperparameter Importance of Quantum Neural Networks Across Small Datasets -- 1 Introduction -- 2 Background -- 2.1 Functional ANOVA -- 2.2 Supervised Learning with Parameterized Quantum Circuits -- 3 Methods -- 3.1 Hyperparameters and Configuration Space -- 3.2 Assessing Hyperparameter Importance -- 3.3 Verifying Hyperparameter Importance -- 4 Dataset and Inclusion Criteria -- 5 Results -- 5.1 Performance Distributions per Dataset -- 5.2 Surrogate Verification -- 5.3 Marginal Contributions -- 5.4 Random Search Verification -- 6 Conclusion -- References -- ImitAL: Learned Active Learning Strategy on Synthetic Data -- 1 Introduction -- 2 Simulating AL on Synthetic Training Data.
3 Training a Neural Network by Imitation Learning -- 3.1 Imitation Learning -- 3.2 Neural Network Input and Output Encoding -- 3.3 Pre-selection -- 4 Evaluation -- 4.1 Experiment Details -- 4.2 Comparison with Other Active Learning Strategies -- 5 Conclusion -- References -- Incremental/Continual Learning -- Predicting Potential Real-Time Donations in YouTube Live Streaming Services via Continuous-Time Dynamic Graph -- 1 Introduction -- 2 Related Work -- 2.1 Online Live Streaming Service -- 2.2 Dynamic Graph Learning -- 3 Methodology -- 3.1 Dataset -- 3.2 Dynamic Graph Generation -- 3.3 Temporal Graph Neural Network -- 3.4 Strategies for Data Imbalance -- 4 Experiments -- 4.1 Dataset Description -- 4.2 Experiment Setup -- 4.3 Baselines -- 4.4 Evaluation -- 4.5 Case Study -- 5 Conclusion -- References -- Semi-supervised Change Point Detection Using Active Learning -- 1 Introduction -- 2 AL-CPD -- 2.1 Algorithm Outline -- 2.2 Selecting Candidate Change Points -- 2.3 Finding New Candidate Change Points -- 3 Experiments -- 3.1 Datasets -- 3.2 Methodology -- 3.3 Q1: Comparison to Existing Change Point Detection Algorithms -- 3.4 Q2: Labelling Effort of AL-CPD -- 3.5 Q3: Contribution of Each Component of AL-CPD -- 3.6 Q4: Sensitivity Analysis -- 4 Conclusion -- References -- Adaptive Neural Networks for Online Domain Incremental Continual Learning -- 1 Introduction -- 2 Related Work -- 3 Online Domain Incremental Networks -- 4 Experiments -- 5 Conclusion -- References -- Incremental Update of Locally Optimal Classification Rules -- 1 Introduction -- 2 The Lord Algorithm -- 3 Incremental Lord -- 3.1 Incremental Updates -- 3.2 Overall Algorithm -- 4 Experiments -- 4.1 Comparison to HoeffdingTree and VFDR -- 4.2 Sensitivity to Parameter Settings -- 5 Conclusion -- References -- Policy Evaluation with Delayed, Aggregated Anonymous Feedback -- 1 Introduction. 2 Related Work -- 3 Preliminaries -- 4 Policy Evaluation with DAAF -- 5 Methodology -- 6 Results -- 7 Discussion and Future Work -- 8 Summary and Conclusions -- References -- Spatial and Temporal Analysis -- Spatial Cross-Validation for Globally Distributed Data -- 1 Introduction -- 2 Related Work -- 3 Spatial k-Fold Cross-Validation -- 4 Evaluation of Performance -- 4.1 Data Sets -- 4.2 Experimental Design -- 4.3 Analysis of Performance -- 5 Conclusions -- References -- .26em plus .1em minus .1emLeveraging Spatio-Temporal Autocorrelation to Improve the Forecasting of the Energy Consumption in Smart Grids -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method -- 3.1 Modeling the Temporal Autocorrelation -- 3.2 Modeling the Spatial Autocorrelation -- 4 Experiments -- 4.1 Experimental Setting -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Elastic Product Quantization for Time Series -- 1 Introduction -- 2 Background -- 2.1 Dynamic Time Warping -- 2.2 Product Quantization -- 3 Approximate Dynamic Time Warping with Product Quantization -- 3.1 Training Phase -- 3.2 Encoding Time Series -- 3.3 Computing Distances Between Time Series -- 3.4 Memory Cost -- 3.5 Pre-alignment of Subspaces -- 4 Data Mining Applications -- 4.1 NN Search with PQ Approximates -- 4.2 Clustering with PQ Approximates -- 5 Experimental Settings -- 6 Experimental Results -- 6.1 Empirical Time Complexity -- 6.2 1NN Classification -- 6.3 Hierarchical Clustering -- 7 Conclusions -- References -- Stress Detection from Wearable Sensor Data Using Gramian Angular Fields and CNN -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Sample Construction -- 2.4 Convolutional Neural Network -- 3 Results -- 3.1 Implementation -- 3.2 Experiments -- 4 Conclusions and Future Work -- References. Multi-attribute Transformers for Sequence Prediction in Business Process Management -- 1 Introduction -- 2 Definitions and Problem Statement -- 3 Related Work -- 4 Proposed Architectures -- 4.1 Encoder Architectures -- 4.2 Simplified Decoder Architectures -- 5 Experiments and Discussion -- 6 Conclusions and Final Remarks -- References -- Social Media Analysis -- Data-Driven Prediction of Athletes' Performance Based on Their Social Media Presence -- 1 Introduction -- 2 Related Work -- 2.1 Social Media as a Mood and Behaviour Detection Proxy -- 2.2 Social Media as a Distraction Factor -- 3 Methodology -- 3.1 Data Selection -- 3.2 Data Preparation -- 3.3 Predictive Significance Analysis -- 3.4 Implementation Details -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Link Prediction with Text in Online Social Networks: The Role of Textual Content on High-Resolution Temporal Data -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Graph Construction and Sequence-Based Framework -- 3.2 Learning Algorithms for Link Prediction in Temporal OSNs -- 3.3 Features for Link Prediction -- 4 Dataset -- 5 Results -- 5.1 Results for Traditional Models -- 5.2 Results for Graph Neural Networks -- 6 Discussion -- References -- Weakly Supervised Named Entity Recognition for Carbon Storage Using Deep Neural Networks -- 1 Introduction -- 2 Overview -- 2.1 Contributions -- 3 Background -- 4 Methodology -- 4.1 Noisy Data Set Creation -- 4.2 Overcoming Noisy Labels Effect -- 5 Evaluation -- 6 Related Work -- 7 Conclusion -- References -- Predicting User Dropout from Their Online Learning Behavior -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Data Set -- 3.2 Features -- 3.3 Pre-processing -- 3.4 Predictive Model -- 3.5 Evaluation -- 4 Results -- 4.1 Predictive Model -- 4.2 Evaluation -- 5 Discussion -- 6 Conclusions -- References. Efficient Multivariate Data Fusion for Misinformation Detection During High Impact Events -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 High-Level Feature Extraction -- 2.3 Multi-modal Data Fusion Framework Based on Independent Vector Analysis -- 2.4 Effective Density Model for Capturing Multi-modal Associations -- 2.5 Classification Procedure -- 3 Results and Discussion -- 3.1 Classification Performance -- 3.2 Explainability -- 4 Conclusion -- References -- Fairness and Outlier Detection -- MQ-OFL: Multi-sensitive Queue-based Online Fair Learning -- 1 Introduction -- 2 Background -- 2.1 Related Work -- 2.2 Fairness Definitions -- 2.3 Gerrymandering -- 2.4 Imbalanced and Drifted Data Stream -- 3 MQ-OFL Framework -- 3.1 Balanced and Fairness-Aware Pre-processing -- 3.2 Classifier Pool -- 3.3 Decision Boundary Adjustment -- 4 Experimental Evaluation -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Experimental Results -- 5 Conclusion -- References -- Multi-fairness Under Class-Imbalance -- 1 Introduction -- 2 Related Work -- 3 Basics and Multi-Max Mistreatment (MMM) Fairness -- 3.1 Multi-Max Mistreatment(MMM) Measure -- 4 Multi-Fairness-Aware Learning -- 4.1 Multi-discrimination-Free Learning Under Class-Imbalance -- 4.2 The MMM-Fair Boosting Post Pareto (MFBPP) Algorithm -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Evaluation Results -- 5.3 Internal Analysis -- 5.4 Flexibility of MFBPP -- 6 Conclusions and Outlook -- References -- When Correlation Clustering Meets Fairness Constraints -- 1 Introduction -- 2 Related Work -- 3 Fairness Constraints in Correlation Clustering -- 3.1 Background on Correlation Clustering -- 3.2 Problem Statement -- 4 Algorithm -- 5 Fairness Evaluation -- 6 Experimental Methodology -- 6.1 Competing Methods -- 6.2 Data -- 6.3 Evaluation Goals -- 6.4 Hyper-parameters and Configurations -- 7 Results. 8 Conclusions. |
| Record Nr. | UNISA-996500065803316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Discovery science : 25th international conference, DS 2022, Montpellier, France, October 10-12, 2022, proceedings / / edited by Poncelet Pascal and Dino Ienco
| Discovery science : 25th international conference, DS 2022, Montpellier, France, October 10-12, 2022, proceedings / / edited by Poncelet Pascal and Dino Ienco |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (576 pages) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Discoveries in science
Research - Data processing |
| ISBN | 3-031-18840-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Keynote Talks -- Unsupervised Model Selection in Outlier Detection: The Elephant in the Room -- Coloring Social Relationships -- 35 Years of 'Scientific Discovery: Computational Explorations of the Creative Processes' - From the Early Days to the State of the Art -- Contents -- Regression and Limited Data -- Model Optimization in Imbalanced Regression -- 1 Introduction -- 2 Related Work -- 3 Imbalanced Regression -- 3.1 Relevance Function -- 3.2 Squared Error Relevance Area (SERA) -- 4 Optimization Loss Function for Imbalanced Regression -- 5 Experimental Study -- 5.1 Experimental Setup -- 5.2 Results on Model Optimization -- 5.3 Results in Out-of-Sample -- 6 Conclusions -- A SERA numerical approximation -- B Tables of Results -- References -- Discovery of Differential Equations Using Probabilistic Grammars -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Algebraic Equations and Numeric Differentiation -- 3.2 Differential Equations and Direct Simulation -- 3.3 Parallel Computation -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusion -- References -- Hyperparameter Importance of Quantum Neural Networks Across Small Datasets -- 1 Introduction -- 2 Background -- 2.1 Functional ANOVA -- 2.2 Supervised Learning with Parameterized Quantum Circuits -- 3 Methods -- 3.1 Hyperparameters and Configuration Space -- 3.2 Assessing Hyperparameter Importance -- 3.3 Verifying Hyperparameter Importance -- 4 Dataset and Inclusion Criteria -- 5 Results -- 5.1 Performance Distributions per Dataset -- 5.2 Surrogate Verification -- 5.3 Marginal Contributions -- 5.4 Random Search Verification -- 6 Conclusion -- References -- ImitAL: Learned Active Learning Strategy on Synthetic Data -- 1 Introduction -- 2 Simulating AL on Synthetic Training Data.
3 Training a Neural Network by Imitation Learning -- 3.1 Imitation Learning -- 3.2 Neural Network Input and Output Encoding -- 3.3 Pre-selection -- 4 Evaluation -- 4.1 Experiment Details -- 4.2 Comparison with Other Active Learning Strategies -- 5 Conclusion -- References -- Incremental/Continual Learning -- Predicting Potential Real-Time Donations in YouTube Live Streaming Services via Continuous-Time Dynamic Graph -- 1 Introduction -- 2 Related Work -- 2.1 Online Live Streaming Service -- 2.2 Dynamic Graph Learning -- 3 Methodology -- 3.1 Dataset -- 3.2 Dynamic Graph Generation -- 3.3 Temporal Graph Neural Network -- 3.4 Strategies for Data Imbalance -- 4 Experiments -- 4.1 Dataset Description -- 4.2 Experiment Setup -- 4.3 Baselines -- 4.4 Evaluation -- 4.5 Case Study -- 5 Conclusion -- References -- Semi-supervised Change Point Detection Using Active Learning -- 1 Introduction -- 2 AL-CPD -- 2.1 Algorithm Outline -- 2.2 Selecting Candidate Change Points -- 2.3 Finding New Candidate Change Points -- 3 Experiments -- 3.1 Datasets -- 3.2 Methodology -- 3.3 Q1: Comparison to Existing Change Point Detection Algorithms -- 3.4 Q2: Labelling Effort of AL-CPD -- 3.5 Q3: Contribution of Each Component of AL-CPD -- 3.6 Q4: Sensitivity Analysis -- 4 Conclusion -- References -- Adaptive Neural Networks for Online Domain Incremental Continual Learning -- 1 Introduction -- 2 Related Work -- 3 Online Domain Incremental Networks -- 4 Experiments -- 5 Conclusion -- References -- Incremental Update of Locally Optimal Classification Rules -- 1 Introduction -- 2 The Lord Algorithm -- 3 Incremental Lord -- 3.1 Incremental Updates -- 3.2 Overall Algorithm -- 4 Experiments -- 4.1 Comparison to HoeffdingTree and VFDR -- 4.2 Sensitivity to Parameter Settings -- 5 Conclusion -- References -- Policy Evaluation with Delayed, Aggregated Anonymous Feedback -- 1 Introduction. 2 Related Work -- 3 Preliminaries -- 4 Policy Evaluation with DAAF -- 5 Methodology -- 6 Results -- 7 Discussion and Future Work -- 8 Summary and Conclusions -- References -- Spatial and Temporal Analysis -- Spatial Cross-Validation for Globally Distributed Data -- 1 Introduction -- 2 Related Work -- 3 Spatial k-Fold Cross-Validation -- 4 Evaluation of Performance -- 4.1 Data Sets -- 4.2 Experimental Design -- 4.3 Analysis of Performance -- 5 Conclusions -- References -- .26em plus .1em minus .1emLeveraging Spatio-Temporal Autocorrelation to Improve the Forecasting of the Energy Consumption in Smart Grids -- 1 Introduction -- 2 Related Work -- 3 The Proposed Method -- 3.1 Modeling the Temporal Autocorrelation -- 3.2 Modeling the Spatial Autocorrelation -- 4 Experiments -- 4.1 Experimental Setting -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Elastic Product Quantization for Time Series -- 1 Introduction -- 2 Background -- 2.1 Dynamic Time Warping -- 2.2 Product Quantization -- 3 Approximate Dynamic Time Warping with Product Quantization -- 3.1 Training Phase -- 3.2 Encoding Time Series -- 3.3 Computing Distances Between Time Series -- 3.4 Memory Cost -- 3.5 Pre-alignment of Subspaces -- 4 Data Mining Applications -- 4.1 NN Search with PQ Approximates -- 4.2 Clustering with PQ Approximates -- 5 Experimental Settings -- 6 Experimental Results -- 6.1 Empirical Time Complexity -- 6.2 1NN Classification -- 6.3 Hierarchical Clustering -- 7 Conclusions -- References -- Stress Detection from Wearable Sensor Data Using Gramian Angular Fields and CNN -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Preprocessing -- 2.3 Sample Construction -- 2.4 Convolutional Neural Network -- 3 Results -- 3.1 Implementation -- 3.2 Experiments -- 4 Conclusions and Future Work -- References. Multi-attribute Transformers for Sequence Prediction in Business Process Management -- 1 Introduction -- 2 Definitions and Problem Statement -- 3 Related Work -- 4 Proposed Architectures -- 4.1 Encoder Architectures -- 4.2 Simplified Decoder Architectures -- 5 Experiments and Discussion -- 6 Conclusions and Final Remarks -- References -- Social Media Analysis -- Data-Driven Prediction of Athletes' Performance Based on Their Social Media Presence -- 1 Introduction -- 2 Related Work -- 2.1 Social Media as a Mood and Behaviour Detection Proxy -- 2.2 Social Media as a Distraction Factor -- 3 Methodology -- 3.1 Data Selection -- 3.2 Data Preparation -- 3.3 Predictive Significance Analysis -- 3.4 Implementation Details -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Link Prediction with Text in Online Social Networks: The Role of Textual Content on High-Resolution Temporal Data -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Graph Construction and Sequence-Based Framework -- 3.2 Learning Algorithms for Link Prediction in Temporal OSNs -- 3.3 Features for Link Prediction -- 4 Dataset -- 5 Results -- 5.1 Results for Traditional Models -- 5.2 Results for Graph Neural Networks -- 6 Discussion -- References -- Weakly Supervised Named Entity Recognition for Carbon Storage Using Deep Neural Networks -- 1 Introduction -- 2 Overview -- 2.1 Contributions -- 3 Background -- 4 Methodology -- 4.1 Noisy Data Set Creation -- 4.2 Overcoming Noisy Labels Effect -- 5 Evaluation -- 6 Related Work -- 7 Conclusion -- References -- Predicting User Dropout from Their Online Learning Behavior -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Data Set -- 3.2 Features -- 3.3 Pre-processing -- 3.4 Predictive Model -- 3.5 Evaluation -- 4 Results -- 4.1 Predictive Model -- 4.2 Evaluation -- 5 Discussion -- 6 Conclusions -- References. Efficient Multivariate Data Fusion for Misinformation Detection During High Impact Events -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 High-Level Feature Extraction -- 2.3 Multi-modal Data Fusion Framework Based on Independent Vector Analysis -- 2.4 Effective Density Model for Capturing Multi-modal Associations -- 2.5 Classification Procedure -- 3 Results and Discussion -- 3.1 Classification Performance -- 3.2 Explainability -- 4 Conclusion -- References -- Fairness and Outlier Detection -- MQ-OFL: Multi-sensitive Queue-based Online Fair Learning -- 1 Introduction -- 2 Background -- 2.1 Related Work -- 2.2 Fairness Definitions -- 2.3 Gerrymandering -- 2.4 Imbalanced and Drifted Data Stream -- 3 MQ-OFL Framework -- 3.1 Balanced and Fairness-Aware Pre-processing -- 3.2 Classifier Pool -- 3.3 Decision Boundary Adjustment -- 4 Experimental Evaluation -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Experimental Results -- 5 Conclusion -- References -- Multi-fairness Under Class-Imbalance -- 1 Introduction -- 2 Related Work -- 3 Basics and Multi-Max Mistreatment (MMM) Fairness -- 3.1 Multi-Max Mistreatment(MMM) Measure -- 4 Multi-Fairness-Aware Learning -- 4.1 Multi-discrimination-Free Learning Under Class-Imbalance -- 4.2 The MMM-Fair Boosting Post Pareto (MFBPP) Algorithm -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Evaluation Results -- 5.3 Internal Analysis -- 5.4 Flexibility of MFBPP -- 6 Conclusions and Outlook -- References -- When Correlation Clustering Meets Fairness Constraints -- 1 Introduction -- 2 Related Work -- 3 Fairness Constraints in Correlation Clustering -- 3.1 Background on Correlation Clustering -- 3.2 Problem Statement -- 4 Algorithm -- 5 Fairness Evaluation -- 6 Experimental Methodology -- 6.1 Competing Methods -- 6.2 Data -- 6.3 Evaluation Goals -- 6.4 Hyper-parameters and Configurations -- 7 Results. 8 Conclusions. |
| Record Nr. | UNINA-9910629276803321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Electrostatic protection of the solar power satellite and rectenna / / Rice University ; prepared for Marshal Space Flight Center
| Electrostatic protection of the solar power satellite and rectenna / / Rice University ; prepared for Marshal Space Flight Center |
| Pubbl/distr/stampa | Washington, D.C. : , : National Aeronautics and Space Administration, Scientific and Technical Information Branch, , 1980 |
| Descrizione fisica | 1 online resource (2 volumes) : illustrations, maps |
| Collana | NASA contractor report |
| Soggetto topico |
Satellite solar power stations
Magnetic fields Lightning conductors Research - Data processing |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. 1. Protection of the solar power satellite -- pt. 2. Lightning protection of the rectenna. |
| Record Nr. | UNINA-9910704227303321 |
| Washington, D.C. : , : National Aeronautics and Space Administration, Scientific and Technical Information Branch, , 1980 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
For attribution-- : developing data attribution and citation practices and standards : summary of an international workshop / / Paul F. Uhlir, rapporteur, Board on Research Data and Information, Policy and Global Affairs, National Research Council of the National Academies
| For attribution-- : developing data attribution and citation practices and standards : summary of an international workshop / / Paul F. Uhlir, rapporteur, Board on Research Data and Information, Policy and Global Affairs, National Research Council of the National Academies |
| Pubbl/distr/stampa | Washington, District of Columbia : , : The National Academies Press, , [2012] |
| Descrizione fisica | 1 online resource (237 p.) |
| Disciplina | 808.02/7 |
| Soggetto topico |
Citation of electronic information resources
Research - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN | 0-309-26729-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Why are the attribution and citation of scientific data important? -- Formal publication of data: an idea whose time has come? -- Attribution and credit: beyond print and citations -- Data citation, technical issues, identification -- Maintaining the scholarly value chain: authenticity, provenance, and trust -- Towards data attribution and citation iin the life sciences -- Data citation in the earth and physical sciences -- Data citation in the social sciences -- Data citation in the humanities: what the problem? -- Three legal mechanisms for sharing data -- Institutional perspective on credit systems for research data -- Issues of time, credit, and peer review -- The DataCite Consortium -- Data citatioin in the Dataverse Network℗ʼ -- Microsoft Academic Search: an overview and future directions -- Data center-library cooperation in data publication in ocean science -- Data citation mechanism and service for scientific data: defining a framework for biodiversity data publishers -- How to cite an earth science dataset? -- Citable publications of scientific data -- The SageCite Project -- Developing data attribution and citation practices and standards: an academic institution perspective -- Data citation and data attribution: a view from the data center perspective -- Roles for libraries in data citation -- Linking data to publications: towards the execution of papers -- Linking, finding, and citing data in astronomy -- Standards and data citations -- Data citation and attribution: a funder's perspective. |
| Record Nr. | UNINA-9910464436703321 |
| Washington, District of Columbia : , : The National Academies Press, , [2012] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
For attribution-- : developing data attribution and citation practices and standards : summary of an international workshop / / Paul F. Uhlir, rapporteur, Board on Research Data and Information, Policy and Global Affairs, National Research Council of the National Academies
| For attribution-- : developing data attribution and citation practices and standards : summary of an international workshop / / Paul F. Uhlir, rapporteur, Board on Research Data and Information, Policy and Global Affairs, National Research Council of the National Academies |
| Pubbl/distr/stampa | Washington, District of Columbia : , : The National Academies Press, , [2012] |
| Descrizione fisica | 1 online resource (237 p.) |
| Disciplina | 808.02/7 |
| Soggetto topico |
Citation of electronic information resources
Research - Data processing |
| ISBN |
0-309-26731-5
0-309-26729-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Why are the attribution and citation of scientific data important? -- Formal publication of data: an idea whose time has come? -- Attribution and credit: beyond print and citations -- Data citation, technical issues, identification -- Maintaining the scholarly value chain: authenticity, provenance, and trust -- Towards data attribution and citation iin the life sciences -- Data citation in the earth and physical sciences -- Data citation in the social sciences -- Data citation in the humanities: what the problem? -- Three legal mechanisms for sharing data -- Institutional perspective on credit systems for research data -- Issues of time, credit, and peer review -- The DataCite Consortium -- Data citatioin in the Dataverse Network℗ʼ -- Microsoft Academic Search: an overview and future directions -- Data center-library cooperation in data publication in ocean science -- Data citation mechanism and service for scientific data: defining a framework for biodiversity data publishers -- How to cite an earth science dataset? -- Citable publications of scientific data -- The SageCite Project -- Developing data attribution and citation practices and standards: an academic institution perspective -- Data citation and data attribution: a view from the data center perspective -- Roles for libraries in data citation -- Linking data to publications: towards the execution of papers -- Linking, finding, and citing data in astronomy -- Standards and data citations -- Data citation and attribution: a funder's perspective. |
| Record Nr. | UNINA-9910789359503321 |
| Washington, District of Columbia : , : The National Academies Press, , [2012] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
For attribution-- : developing data attribution and citation practices and standards : summary of an international workshop / / Paul F. Uhlir, rapporteur, Board on Research Data and Information, Policy and Global Affairs, National Research Council of the National Academies
| For attribution-- : developing data attribution and citation practices and standards : summary of an international workshop / / Paul F. Uhlir, rapporteur, Board on Research Data and Information, Policy and Global Affairs, National Research Council of the National Academies |
| Pubbl/distr/stampa | Washington, District of Columbia : , : The National Academies Press, , [2012] |
| Descrizione fisica | 1 online resource (237 p.) |
| Disciplina | 808.02/7 |
| Soggetto topico |
Citation of electronic information resources
Research - Data processing |
| ISBN |
0-309-26731-5
0-309-26729-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Why are the attribution and citation of scientific data important? -- Formal publication of data: an idea whose time has come? -- Attribution and credit: beyond print and citations -- Data citation, technical issues, identification -- Maintaining the scholarly value chain: authenticity, provenance, and trust -- Towards data attribution and citation iin the life sciences -- Data citation in the earth and physical sciences -- Data citation in the social sciences -- Data citation in the humanities: what the problem? -- Three legal mechanisms for sharing data -- Institutional perspective on credit systems for research data -- Issues of time, credit, and peer review -- The DataCite Consortium -- Data citatioin in the Dataverse Network℗ʼ -- Microsoft Academic Search: an overview and future directions -- Data center-library cooperation in data publication in ocean science -- Data citation mechanism and service for scientific data: defining a framework for biodiversity data publishers -- How to cite an earth science dataset? -- Citable publications of scientific data -- The SageCite Project -- Developing data attribution and citation practices and standards: an academic institution perspective -- Data citation and data attribution: a view from the data center perspective -- Roles for libraries in data citation -- Linking data to publications: towards the execution of papers -- Linking, finding, and citing data in astronomy -- Standards and data citations -- Data citation and attribution: a funder's perspective. |
| Record Nr. | UNINA-9910811993103321 |
| Washington, District of Columbia : , : The National Academies Press, , [2012] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
GigaByte
| GigaByte |
| Pubbl/distr/stampa | [Hong Kong] : , : BGI |
| Descrizione fisica | 1 online resource |
| Soggetto topico |
Information storage and retrieval systems
Research - Data processing Computer software Systèmes d'information Logiciels Biological Science Disciplines Big Data |
| Soggetto genere / forma |
Periodicals.
Periodical |
| ISSN | 2709-4715 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910439026103321 |
| [Hong Kong] : , : BGI | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
GigaByte
| GigaByte |
| Pubbl/distr/stampa | [Hong Kong] : , : BGI |
| Descrizione fisica | 1 online resource |
| Soggetto topico |
Information storage and retrieval systems
Research - Data processing Computer software Systèmes d'information Logiciels Biological Science Disciplines Big Data |
| Soggetto genere / forma |
Periodicals.
Periodical |
| ISSN | 2709-4715 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996404405603316 |
| [Hong Kong] : , : BGI | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Issues for science and engineering researchers in the digital age [[electronic resource] /] / [Ad Hoc Committee on Being a Scholar in the Digital Age]
| Issues for science and engineering researchers in the digital age [[electronic resource] /] / [Ad Hoc Committee on Being a Scholar in the Digital Age] |
| Pubbl/distr/stampa | Washington, D.C., : National Academy Press, c2001 |
| Descrizione fisica | 1 online resource (69 p.) |
| Disciplina | 502/.85 |
| Altri autori (Persone) | DuderstadtJames J. <1942-> |
| Collana | The compass series |
| Soggetto topico |
Research - Data processing
Engineering - Research - Data processing |
| Soggetto genere / forma | Electronic books. |
| ISBN | 0-309-51302-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Matter; Preface; Contents; 1 A Revolution in the Tools of Scientific and Engineering Research; 2 The Research Process in a Digital World; 3 A Digital Infrastructure to Support Tomorrow's Research Communities; 4 Changing Expectations of the Researcher; References; APPENDIX A Committee Member Biographies |
| Record Nr. | UNINA-9910456166603321 |
| Washington, D.C., : National Academy Press, c2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
