Data Mining

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

Includes topics such as: Real-World Data Mining Applications, Web, Text, Clustering, and Multimedia Mining. Les mer
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Includes topics such as: Real-World Data Mining Applications, Web, Text, Clustering, and Multimedia Mining.



Session: Real-World Data Mining Applications, Challenges, and Perspectives
1) Mechanical Property Classification of Vapor-Grown Carbon Nanofiber/Vinyl Ester Nanocomposites Using Support Vector Machines
2) APPES Maps as Tools for Quantifying Performance of Truck Drivers
3) Distributed Evolutionary Algorithm for Clustering Multi-Characteristic Social Networks
4) Implementation of Artificial Neural Networks in MapReduce Optimization
5) A New Effective Information Decomposition Approach for Missing Data Recovery
6) Predicting Causes of Traffic Road Accidents Using Multi-class Support Vector Machines
7) Gold, Oil and the S&P 500 Index: Calm to Crisis and Back
8) Using Bootstrap Aggregated Neural Networks for Peripheral Nerve Injury Treatment
9) The Significance of the Race Factor in Breast Cancer Prognosis
10) A Proposed Data Mining Model for the Associated Factors of Alzheimer's Disease
11) Automated Statistical Data Mining of a Real World Landslide Detection System
Session: Classification, Clustering, Association
1) Feature Selection by Tree Search of Correlation-Adjusted Class Distancesli>
2) Multi-Level Synthesis of Frequent Rules from Different Databases Using a Clustering Approachli>
3) Mammogram Classification Using Association Rule Mining
4) Feature Engineering for Supervised Link Prediction on Dynamic Social Networks
5) A Flexible Feature Selection Framework for Improving Breast Cancer Classification from Sparse Spectral Count Proteomic Data
6) Optimization of an Individual Re-identification Modeling Process Using Biometric Features
7) More Reliable Over-sampled Synthetic Data Instances by Using Artificial Neural Networks for a Minority Class
8) Entropy Based Adaptive Outlier Detection Technique for Data Streams
Session: Web, Text, Multimedia Mining
1) Sub-Net Identification for Text Refinement and Text Meaning Discovery in Social Media Analytics
2) Semi-automatic Metadata Extraction from Scientific Journal Article for Full-text XML Conversion
3) The Authorship of Audacity: Data Mining and Stylometric Analysis of Barack Obama Speeches
4) Text Ctegorization using Topic Model and Ontology Networks
5) Personalizing Query Refinement Based on Latent Tasks
6) Positive Unlabeled Learning to Discover Relevant Documents Using Topic Models for Feature Selection
7) A Framework For Flexible Educational Data Mining
Session: Late Breaking Papers and Position Papers: Data Mining
1) Author Attribution of Thomas Paine Work
2) Identifying Outliers in Human Movement Trajectories Clustered By Hausdorff Distance
3) Automatic Solar Cavity Detection Using Haar Cascade Classifier
4) Processing of Kuala Lumpur Stock Exchange Resident on Hadoop MapReduce
5) Generating Well-Behaved Learning Curves: An Empirical Study
6) Determination of Fake Reviews in Hospitality Sector

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.