Advances in Data Mining. Applications and Theoretical Aspects

1. Front Matter

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2. Data Mining in Medicine and Biology

   1. Application of Classification Algorithms on IDDM Rat Data

      • Rainer Schmidt, Heike Weiss, Georg Fuellen

      Pages 1-8

   2. Research Themes in the Case-Based Reasoning in Health Sciences Core Literature

      • Isabelle Bichindaritz

      Pages 9-23

   3. Research on Application of Data Mining Methods to Diagnosing Gastric Cancer

      • Arnis Kirshners, Serge Parshutin, Marcis Leja

      Pages 24-37

   4. SOHAC: Efficient Storage of Tick Data That Supports Search and Analysis

      • Gabor I. Nagy, Krisztian Buza

      Pages 38-51

3. Data Mining for Energy Industry

   1. Electricity Consumption Time Series Profiling: A Data Mining Application in Energy Industry

      • Hongyan Liu, Zhiyuan Yao, Tomas Eklund, Barbro Back

      Pages 52-66

   2. Wind Turbines Fault Diagnosis Using Ensemble Classifiers

      • Pedro Santos, Luisa F. Villa, Aníbal Reñones, Andrés Bustillo, Jesús Maudes

      Pages 67-76

4. Data Mining in Traffic and Logistic

   1. Bus Bunching Detection by Mining Sequences of Headway Deviations

      • Luís Moreira-Matias, Carlos Ferreira, João Gama, João Mendes-Moreira, Jorge Freire de Sousa

      Pages 77-91

5. Data Mining in Telecommunication

   1. Detecting Abnormal Patterns in Call Graphs Based on the Aggregation of Relevant Vertex Measures

      • Ronnie Alves, Pedro Ferreira, Joel Ribeiro, Orlando Belo

      Pages 92-102

6. Data Mining in Engineering

   1. Real-Time Mass Flow Estimation in Circulating Fluidized Bed

      • Andriy Ivannikov, Mikko Jegoroff, Tommi Kärkkäinen

      Pages 103-112

   2. Representation in Case-Based Reasoning Applied to Control Reconfiguration

      • Ons Lejri, Moncef Tagina

      Pages 113-120

   3. The Influence of Input and Output Measurement Noise on Batch-End Quality Prediction with Partial Least Squares

      • Jef Vanlaer, Pieter Van den Kerkhof, Geert Gins, Jan F. M. Van Impe

      Pages 121-135

7. Theory in Data Mining

   1. An Evolving Associative Classifier for Incomplete Database

      • Kaoru Shimada

      Pages 136-150

   2. Improving Classifier Performance by Knowledge-Driven Data Preparation

      • Laura Welcker, Stephan Koch, Frank Dellmann

      Pages 151-165

   3. CWFM: Closed Contingency Weighted Frequent Itemsets Mining

      • Eunkyoung Park, Younghee Kim, Ieejoon Kim, Jaeyeol Yoon, Jiyeon Lim, Ungmo Kim

      Pages 166-177

   4. Prognostic Modeling with High Dimensional and Censored Data

      • Leon Bobrowski, Tomasz Łukaszuk

      Pages 178-193

8. Theory in Data Mining: Clustering

   1. \(\mathcal{SHACUN}\): Semi-supervised Hierarchical Active Clustering Based on Ranking Constraints

      • Eya Ben Ahmed, Ahlem Nabli, Faïez Gargouri

      Pages 194-208

   2. A Minimum Spanning Tree-Inspired Clustering-Based Outlier Detection Technique

      • Xiaochun Wang, Xia Li Wang, D. Mitch Wilkes

      Pages 209-223

9. Theory in Data Mining: Association Rule Mining and Decision Rule Mining

   1. ML-DS: A Novel Deterministic Sampling Algorithm for Association Rules Mining

      • Samir A. Mohamed Elsayed, Sanguthevar Rajasekaran, Reda A. Ammar

      Pages 224-235

   2. Decision Rules Development Using Set of Generic Operations Approach

      • Wiesław Paja, Mariusz Wrzesień

      Pages 236-242

This book constitutes the refereed proceedings of the 12th Industrial Conference on Data Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised full papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on data mining in medicine and biology; data mining for energy industry; data mining in traffic and logistic; data mining in telecommunication; data mining in engineering; theory in data mining; theory in data mining: clustering; theory in data mining: association rule mining and decision rule mining.

• case-based reasoning
• data warehouse
• learning algorithms
• rule optimization
• self-organizing maps

• Institute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

  Petra Perner

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