Tentative Table of Contents

Foreword

David Bell, Queen's University Belfast, UK

Part I: Introduction

Chapter 1: Association Rules: An Overview

Paul D. McNicholas, University of Guelph, Canada
Yanchang Zhao, University of Technology, Sydney, Australia

Part II: Identifying Interesting Rules

Chapter 2: From Change Mining to Relevance Feedback - A Unified View on Assessing Rule Interestingness

Mirko Boettcher, University of Magdeburg, Germany
Georg Ruß, University of Magdeburg, Germany
Detlef Nauck, BT Group plc, United Kingdom
Rudolf Kruse, University of Magdeburg, Germany 

Chapter 3: Combining Data-driven and User-driven Evaluation Measures to Identify Interesting Rules

Solange Oliveira Rezende, University of São Paulo, Brazil
Edson Augusto Melanda, Federal University of São Carlos, Brazil
Magaly Lika Fujimoto, University of São Paulo, Brazil
Roberta Akemi Sinoara, University of São Paulo, Brazil
Veronica Oliveira de Carvalho, University of Oeste Paulista, Brazil 

Chapter 4: Semantics-based classification of rule interestingness measures

Julien Blanchard, Polytechnic School of Nantes University, France
Fabrice Guillet, Polytechnic School of Nantes University, France
Pascale Kuntz, Polytechnic School of Nantes University, France

Part III: Post-Analysis and Post-Mining of Association Rules

Chapter 5: Post-processing for Rule Reduction using Closed Set

Huawen Liu, Jilin University, P.R. China
Jigui Sun, Jilin University, P.R. China
Huijie Zhang, Northeast Normal University, P.R. China 

Chapter 6: A Conformity Measure using Background Knowledge for Association Rules: Application to Text Mining

Hacène Cherfi, INRIA Sophia Antipolis, France
Amedeo Napoli, LORIA - INRIA, France 
Yannick Toussaint, LORIA - INRIA, France

Chapter 7: Continuous Post-Mining of Association Rules in a Data Stream Management System

Hetal Thakkar, University of California, Los Angeles, USA
Barzan Mozafari, University of California, Los Angeles, USA
Carlo Zaniolo, University of California, Los Angeles, USA

Chapter 8: QROC – A variation of ROC space to analyze item set costs/benefits in association rules

Ronaldo C. Prati, University of São Paulo, Brazil

Part IV: Rule Selection for Classification

Chapter 9: Variations on Associative Classifiers and Classification Results Analyses

Maria-Luiza Antonie, University of Alberta, Canada
David Chodos, University of Alberta, Canada
Osmar Zaïane, University of Alberta, Canada 

Chapter 10: Selection of High Quality Rules in Associative Classification

Silvia Chiusano, Politecnico di Torino, Italy
Paolo Garza, Politecnico di Torino, Italy

Part V: Visualization and Representationof association rules

Chapter 11: Meta-knowledge based approach for an interactive visualization of large amounts of association rules

Sadok Ben Yahia, Faculty of Sciences of Tunis, Tunisia
Olivier Couturier, Rue de l’université, France
Tarek Hamrouni, Faculty of Sciences of Tunis, Tunisia
Engelbert Mephu Nguifo, Rue de l’université, France 

Chapter 12: Visualization to Assist the Generation and Exploration of Association Rules

Claudio Haruo Yamamoto, Universidade de São Paulo, Brazil
Maria Cristina Ferreira de Oliveira, Universidade de São Paulo, Brazil
Solange Oliveira Rezende, Universidade de São Paulo, Brazil 

Chapter 13: Frequent closed itemsets based condensed representations for association rules

Nicolas Pasquier, Université de Nice, France

Part VI: Maintenance of Association Rules and New Forms of Association Rules

Chapter 14: Maintenance of frequent patterns: a survey

Mengling Feng, Nanyang Technological University, Singapore
Jinyan Li, Nanyang Technological University, Singapore,
Guozhu Dong, Wright State University, USA
Limsoon Wong, National University of Singapore, Singapore

Chapter 15: Mining Conditional Contrast Patterns

Guozhu Dong, Wright State University, USA
Jinyan Li, Nanyang Technological University, Singapore
Guimei Liu, National University of Singapore, Singapore
Limsoon Wong, National University of Singapore, Singapore 

Chapter 16: Multidimensional model-based decision rules mining

Qinrong Feng, Tongji University, China
Duoqian Miao, Tongji University, China
Ruizhi Wang, Tongji University, China