New Frontiers in Mining Complex Patterns

1. Front Matter

   Pages I-XIV

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2. Feature Selection and Induction

   1. Front Matter

      Pages 1-1

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   2. Feature Induction and Network Mining with Clustering Tree Ensembles

      • Konstantinos Pliakos, Celine Vens

      Pages 3-18

   3. Ranking to Learn:

      • Giorgio Roffo, Simone Melzi

      Pages 19-35

3. Classification and Prediction

   1. Front Matter

      Pages 37-37

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   2. Bayesian Confirmation Measures in Rule-Based Classification

      • Dariusz Brzezinski, Zbigniew Grudziński, Izabela Szczęch

      Pages 39-53

   3. Audio-Based Speed Change Classification for Vehicles

      • Elżbieta Kubera, Alicja Wieczorkowska, Tomasz Słowik, Andrzej Kuranc, Krzysztof Skrzypiec

      Pages 54-68

   4. A Statistical Approach to Speaker Identification in Forensic Phonetics

      • Fabio Leuzzi, Giovanni Tessitore, Stefano Delfino, Claudio Fusco, Massimo Gneo, Gianpaolo Zambonini et al.

      Pages 69-83

   5. Increasing the Interpretability of Rules Induced from Imbalanced Data by Using Bayesian Confirmation Measures

      • Krystyna Napierała, Jerzy Stefanowski, Izabela Szczȩch

      Pages 84-98

   6. Analyzing Time-Decay Effects of Mediating-Objects in Creating Trust-Links

      • Hiroki Takahashi, Masahiro Kimura

      Pages 99-114

4. Clustering

   1. Front Matter

      Pages 115-115

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   2. Predicting the Primary Medical Procedure Through Clustering of Patients’ Diagnoses

      • Mamoun Almardini, Ayman Hajja, Zbigniew W. Raś, Lina Clover, David Olaleye

      Pages 117-131

   3. Feature Clustering for Extreme Events Analysis, with Application to Extreme Stream-Flow Data

      • Maël Chiapino, Anne Sabourin

      Pages 132-147

   4. Profiling Human Behavior Through Multidimensional Latent Factor Modeling

      • Massimo Guarascio, Francesco Sergio Pisani, Ettore Ritacco, Pietro Sabatino

      Pages 148-162

   5. Multi-view Approach to Parkinson’s Disease Quality of Life Data Analysis

      • Anita Valmarska, Dragana Miljkovic, Marko Robnik-Šikonja, Nada Lavrač

      Pages 163-178

5. Pattern Discovery

   1. Front Matter

      Pages 179-179

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   2. Subgraph Mining for Anomalous Pattern Discovery in Event Logs

      • Laura Genga, Domenico Potena, Orazio Martino, Mahdi Alizadeh, Claudia Diamantini, Nicola Zannone

      Pages 181-197

   3. Mining Spatio-Temporal Patterns of Periodic Changes in Climate Data

      • Corrado Loglisci, Michelangelo Ceci, Angelo Impedovo, Donato Malerba

      Pages 198-212

   4. Mining Keystroke Timing Pattern for User Authentication

      • Saket Maheshwary, Vikram Pudi

      Pages 213-227

6. Applications

   1. Front Matter

      Pages 229-229

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This book features a collection of revised and significantly extended versions of the papers accepted for presentation at the 5th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2016, held in conjunction with ECML-PKDD 2016 in Riva del Garda, Italy, in September 2016. The book is composed of five parts: feature selection and induction; classification prediction; clustering; pattern discovery; applications.

 

• data mining
• ensemble methods
• knowledge discovery
• machine learning
• parallel algorithms
• classification
• clustering
• data stream mining
• feature selection
• first-order logic
• logic programming
• metalearning
• multi-task learning
• network analysis
• semantic similarity measures
• supervised learning
• support vector machines
• text mining heuristics
• time series analysis
• validation

• Università degli Studi di Bari Aldo Moro, Bari, Italy

  Annalisa Appice, Michelangelo Ceci, Corrado Loglisci

• ICAR-CNR, Rende, Italy

  Elio Masciari

• University of North Carolina, Charlotte, USA

  Zbigniew W. Raś

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