Data Warehousing and Knowledge Discovery

1. Front Matter

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2. Modeling and ETL

   1. An Analytics-Aware Conceptual Model for Evolving Graphs

      • Amine Ghrab, Sabri Skhiri, Salim Jouili, Esteban Zimányi

      Pages 1-12

   2. Declarative Expression and Optimization of Data-Intensive Flows

      • Georgia Kougka, Anastasios Gounaris

      Pages 13-25

   3. Tabular Web Data: Schema Discovery and Integration

      • Prudhvi Janga, Karen C. Davis

      Pages 26-33

3. Query Optimization and Parallelism

   1. Uncoupled MapReduce: A Balanced and Efficient Data Transfer Model

      • Jie Zhang, Maosen Sun, Jian Lin, Li Zha

      Pages 34-45

   2. Efficient Evaluation of Ad-Hoc Range Aggregates

      • Christian Ammendola, Michael H. Böhlen, Johann Gamper

      Pages 46-59

   3. SPIN: Concurrent Workload Scaling over Data Warehouses

      • João Pedro Costa, Pedro Furtado

      Pages 60-71

4. Spatial Data Warehouses and Applications

   1. Lily: A Geo-Enhanced Library for Location Intelligence

      • Matteo Golfarelli, Marco Mantovani, Federico Ravaldi, Stefano Rizzi

      Pages 72-83

   2. Discovering Co-location Patterns in Datasets with Extended Spatial Objects

      • Aibek Adilmagambetov, Osmar R. Zaiane, Alvaro Osornio-Vargas

      Pages 84-96

   3. SOLAP4epidemiologist: A Spatial Data Warehousing Application in Epidemiology Domain

      • Assuntina Cembalo, Michele Ferrucci, Francesca Maria Pisano, Gianpaolo Pigliasco

      Pages 97-109

5. Text Mining and OLAP

   1. Document Difficulty Framework for Semi-automatic Text Classification

      • Miguel Martinez-Alvarez, Alejandro Bellogin, Thomas Roelleke

      Pages 110-121

   2. Knowledge-Free Table Summarization

      • Dino Ienco, Yoann Pitarch, Pascal Poncelet, Maguelonne Teisseire

      Pages 122-133

6. Recommendation and Prediction

   1. Predicting Your Next OLAP Query Based on Recent Analytical Sessions

      • Marie-Aude Aufaure, Nicolas Kuchmann-Beauger, Patrick Marcel, Stefano Rizzi, Yves Vanrompay

      Pages 134-145

   2. Where Will You Go? Mobile Data Mining for Next Place Prediction

      • João Bártolo Gomes, Clifton Phua, Shonali Krishnaswamy

      Pages 146-158

   3. An Extended Local Hierarchical Classifier for Prediction of Protein and Gene Functions

      • Luiz Henrique de Campos Merschmann, Alex Alves Freitas

      Pages 159-171

7. Data Mining Optimization and Machine Learning Techniques

   1. Supervised Dimensionality Reduction via Nonlinear Target Estimation

      • Josif Grabocka, Lucas Drumond, Lars Schmidt-Thieme

      Pages 172-183

   2. Concurrent Execution of Data Mining Queries for Spatial Collocation Pattern Discovery

      • Pawel Boinski, Maciej Zakrzewicz

      Pages 184-195

   3. Depth-First Traversal over a Mirrored Space for Non-redundant Discriminative Itemsets

      • Yoshitaka Kameya, Hiroki Asaoka

      Pages 196-208

8. Mining and Processing Data Stream

   1. Stream Mining of Frequent Patterns from Delayed Batches of Uncertain Data

      • Fan Jiang, Carson Kai-Sang Leung

      Pages 209-221

   2. Fast Causal Network Inference over Event Streams

      • Saurav Acharya, Byung Suk Lee

      Pages 222-235

This book constitutes the refereed proceedings of the 15th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2013 held in Prague, Czech Republic, in August 2013.
The 24 revised full papers and 8 short papers presented were carefully reviewed and selected from 89 submissions. The papers are organized in topical sections on modeling and ETL, query optimization and parallelism, spatial data warehouses and applications, text mining and OLAP, recommendation and prediction, data mining optimization and machine learning techniques, mining and processing data streams, clustering and data mining applications, social network and graph mining, and event sequence and Web mining.

• bioinformatics
• community detection
• conceptual modeling
• event streams
• information retrieval

• LIAS/ISAE-ENSMA, Futuroscope Chasseneuil Cedex, France

  Ladjel Bellatreche

• IBM India Research Lab, New Delhi, India

  Mukesh K. Mohania

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