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Data Mining

Stahlbock Robert Abou-Nasr Mahmoud
Heftet / 2015 / Engelsk

Produktdetaljer

ISBN
9781601322395
Publisert
2015-05-01
Utgiver
Vendor
C. S. R. E. A.
Høyde
279 mm
Bredde
203 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
264

Redaktør
Stahlbock Robert
Abou-Nasr Mahmoud

Om bidragsyterne

Hamid R. Arabnia is Professor, Computer Science; Editor-in-Chief, The Journal of Supercomputing (Springer); Elected Fellow, Int'l Society of Intelligent Biological Medicine (ISIBM); The University of Georgia, Department of Computer Science.

Data Mining

Stahlbock Robert Abou-Nasr Mahmoud
Heftet / 2015 / Engelsk
Stahlbock Robert Abou-Nasr Mahmoud
Heftet / 2015 / Engelsk
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Data Mining is a compendium of articles and papers that were presented at DMIN '13, an international conference that serves researchers, scholars, professionals, students, and academicians.

Selected topics include:
  • Real-World Data Mining Applications, Challenges, and Perspectives
  • Segmentation, Clustering, Association + Web / Text / Multimedia Mining
  • Regression And Classification
  • Filtering, Feature Selection, Integration, Ensembles
Les mer
A compendium of articles and papers presented at DMIN ’13. Selected topics include Real-World Data Mining Applications, Challenges, and Perspectives; Segmentation, Clustering, Association + Web / Text / Multimedia Mining; Regression And Classification; Filtering, Feature Selection, Integration, Ensembles.
Les mer
  • Session: Real-World Data Mining Applications, Challenges, and Perspectives
  • 1) Maintenance Knowledge Management with Fusion of CMMS and CM
  • 2) Sentimental Analysis on Turkish Blogs via Ensemble Classifier
  • 3) Reliable Probabilistic Classification of Mammographic Masses Using Random Forests
  • 4) Identifying Patterns and Anomalies in Delayed Neutron Monitor Data of Nuclear Power Plant
  • 5) Alleviating the Class Imbalance Problem in Data Mining
  • 6) Efficiency of Crop Yield Forecasting Depending on the Moment of Prediction based on Large Remote Sensing Data set
  • 7) Neural Network Forecasting with the S&P 500 Index Across Decades
  • 8) Data Uncertainty Handling in High Level Information Fusion
  • 9) A Preliminary Approach to Study the Causality of Freezing of Gait for Parkinson's: Bayesian Belief Network Approach
  • 10) Evaluation of Monte Carlo Subspace Clustering with OpenSubspace
  • 11) MineTool-3DM2: An Algorithm for Data Mining of 3D Simulation Data
  • 12) Actions Ontology System for Action Rules Discovery in Mammographic Mass Data
  • 13) GDP Forecasting through Data Mining of Seaport Export-Import Records
  • 14) Association Rule Mining for Finding Correlations Among People
  • 15) Toward Sustainable High-Yield Agriculture via Intelligent Control Systems
  • 16) Extending Local Similarity Indexes with KNN for Link Prediction
  • 17) A New Simple Classification Algorithm enabling a New Approach for Identification of Virtual Bullying
  • 18) Using Data Mining to Analyze Donation Data for a Local Food Bank
  • 19) Flash Reactivity: Adaptative models in recommender systems
  • 20) Analysis of Truck Compressor Failures Based on Logged Vehicle Data
  • 21) Proposed Business Intelligence Models for Medical Risk Assessment Case study of Venous Thrombosis Disease in Egypt
  • 22) Improve the Quality of Product Recommendation based on Multi-channel CRM for E-commerce
  • 23) Using Recursive Sorting to Improve Accuracy of Memory-based Collaborative Filtering Recommendations
  • Session: Segmentation, Clustering, Association + Web / Text / Multimedia Mining
  • 1) Mining for Hydrologic Features in LiDAR Data
  • 2) Role of Social Media in Early Warning of Norovirus Outbreaks: A Longitudinal Twitter-Based Infoveillance
  • 3) Spatial-Temporal Clustering of a Self-Organizing Map
  • 4) An Evolutionary Associative Contrast Rule Mining Method for Incomplete Database
  • 5) Hierarchical Video Indexing And Retrieval System
  • 6) A Novel Query Suggestion Method Based On Sequence Similarity and Transition Probability
  • Session: Regression and Classification
  • 1) A Multi-scale Nonparametric/Parametric Hybrid Recognition Strategy with Multi-category Posterior Probability Estimation
  • 2) SVM-Based Approaches for Predictive Modeling of Survival Data
  • 3) Large Scale Visual Classification with Parallel, Imbalanced Bagging of Incremental LIBLINEAR SVM
  • 4) Gaussian Process Regression with Dynamic Active Set and Its Application to Anomaly Detection
  • 5) A Study of kNN using ICU Multivariate Time Series Data
  • 6) Genetic Algorithms and Classification Trees in Feature Discovery: Diabetes and the NHANES database
  • Session: Filtering, Feature Selection, Integration, Ensembles
  • 1) Isolating Matrix Sparsity in Collaborative Filtering Ratings Matrices
  • 2) A Novel Randomized Feature Selection Algorithm
  • 3) Fraud Detection Using Reputation Features, SVMs, and Random Forests
  • 4) A Novel Ensemble Selection Technique for Weak Classifiers
  • 5) Labeled Subgraph Matching Using Degree Filtering
  • 6) Social Network Anonymization and Influence Preservation
Les mer

Relaterte produkter

Data Mining is a compendium of articles and papers that were presented at DMIN '13, an international conference that serves researchers, scholars, professionals, students, and academicians.

Selected topics include:
  • Real-World Data Mining Applications, Challenges, and Perspectives
  • Segmentation, Clustering, Association + Web / Text / Multimedia Mining
  • Regression And Classification
  • Filtering, Feature Selection, Integration, Ensembles
Les mer
A compendium of articles and papers presented at DMIN ’13. Selected topics include Real-World Data Mining Applications, Challenges, and Perspectives; Segmentation, Clustering, Association + Web / Text / Multimedia Mining; Regression And Classification; Filtering, Feature Selection, Integration, Ensembles.
Les mer
  • Session: Real-World Data Mining Applications, Challenges, and Perspectives
  • 1) Maintenance Knowledge Management with Fusion of CMMS and CM
  • 2) Sentimental Analysis on Turkish Blogs via Ensemble Classifier
  • 3) Reliable Probabilistic Classification of Mammographic Masses Using Random Forests
  • 4) Identifying Patterns and Anomalies in Delayed Neutron Monitor Data of Nuclear Power Plant
  • 5) Alleviating the Class Imbalance Problem in Data Mining
  • 6) Efficiency of Crop Yield Forecasting Depending on the Moment of Prediction based on Large Remote Sensing Data set
  • 7) Neural Network Forecasting with the S&P 500 Index Across Decades
  • 8) Data Uncertainty Handling in High Level Information Fusion
  • 9) A Preliminary Approach to Study the Causality of Freezing of Gait for Parkinson's: Bayesian Belief Network Approach
  • 10) Evaluation of Monte Carlo Subspace Clustering with OpenSubspace
  • 11) MineTool-3DM2: An Algorithm for Data Mining of 3D Simulation Data
  • 12) Actions Ontology System for Action Rules Discovery in Mammographic Mass Data
  • 13) GDP Forecasting through Data Mining of Seaport Export-Import Records
  • 14) Association Rule Mining for Finding Correlations Among People
  • 15) Toward Sustainable High-Yield Agriculture via Intelligent Control Systems
  • 16) Extending Local Similarity Indexes with KNN for Link Prediction
  • 17) A New Simple Classification Algorithm enabling a New Approach for Identification of Virtual Bullying
  • 18) Using Data Mining to Analyze Donation Data for a Local Food Bank
  • 19) Flash Reactivity: Adaptative models in recommender systems
  • 20) Analysis of Truck Compressor Failures Based on Logged Vehicle Data
  • 21) Proposed Business Intelligence Models for Medical Risk Assessment Case study of Venous Thrombosis Disease in Egypt
  • 22) Improve the Quality of Product Recommendation based on Multi-channel CRM for E-commerce
  • 23) Using Recursive Sorting to Improve Accuracy of Memory-based Collaborative Filtering Recommendations
  • Session: Segmentation, Clustering, Association + Web / Text / Multimedia Mining
  • 1) Mining for Hydrologic Features in LiDAR Data
  • 2) Role of Social Media in Early Warning of Norovirus Outbreaks: A Longitudinal Twitter-Based Infoveillance
  • 3) Spatial-Temporal Clustering of a Self-Organizing Map
  • 4) An Evolutionary Associative Contrast Rule Mining Method for Incomplete Database
  • 5) Hierarchical Video Indexing And Retrieval System
  • 6) A Novel Query Suggestion Method Based On Sequence Similarity and Transition Probability
  • Session: Regression and Classification
  • 1) A Multi-scale Nonparametric/Parametric Hybrid Recognition Strategy with Multi-category Posterior Probability Estimation
  • 2) SVM-Based Approaches for Predictive Modeling of Survival Data
  • 3) Large Scale Visual Classification with Parallel, Imbalanced Bagging of Incremental LIBLINEAR SVM
  • 4) Gaussian Process Regression with Dynamic Active Set and Its Application to Anomaly Detection
  • 5) A Study of kNN using ICU Multivariate Time Series Data
  • 6) Genetic Algorithms and Classification Trees in Feature Discovery: Diabetes and the NHANES database
  • Session: Filtering, Feature Selection, Integration, Ensembles
  • 1) Isolating Matrix Sparsity in Collaborative Filtering Ratings Matrices
  • 2) A Novel Randomized Feature Selection Algorithm
  • 3) Fraud Detection Using Reputation Features, SVMs, and Random Forests
  • 4) A Novel Ensemble Selection Technique for Weak Classifiers
  • 5) Labeled Subgraph Matching Using Degree Filtering
  • 6) Social Network Anonymization and Influence Preservation
Les mer

Produktdetaljer

ISBN
9781601322395
Publisert
2015-05-01
Utgiver
Vendor
C. S. R. E. A.
Høyde
279 mm
Bredde
203 mm
Aldersnivå
U, 05
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
264

Redaktør
Stahlbock Robert
Abou-Nasr Mahmoud

Om bidragsyterne

Hamid R. Arabnia is Professor, Computer Science; Editor-in-Chief, The Journal of Supercomputing (Springer); Elected Fellow, Int'l Society of Intelligent Biological Medicine (ISIBM); The University of Georgia, Department of Computer Science.

Relaterte produkter