Data Mining

Robert Stahlbock (Redaktør) ; Gary M. Weiss (Redaktør) ; Mahmoud Abou-Nasr (Redaktør) ; Hamid R. Arabnia (Redaktør)

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.
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Vår pris: 496,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 21 dager

Om boka

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

Fakta

Innholdsfortegnelse

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

Om forfatteren

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.