InhaltsangabePreface. Acknowledgments. Contributors. 1 INTRODUCTION (Lawrence B. Holder and Diane J. Cook). Part I GRAPHS. 2 GRAPH MATCHING--EXACT AND ERROR-TOLERANT METHODS AND THE AUTOMATIC LEARNING OF EDIT COSTS (Horst Bunke and Michel Neuhaus). 3 GRAPH VISUALIZATION AND DATA MINING (Walter Didimo and Giuseppe Liotta). 4 GRAPH PATTERNS AND THE R-MAT GENERATOR (Deepayan Chakrabarti and Christos Faloutsos). Part II MINING TECHNIQUES. 5 DISCOVERY OF FREQUENT SUBSTRUCTURES (Xifeng Yan and Jiawei Han). 6 FINDING TOPOLOGICAL FREQUENT PATTERNS FROM GRAPH DATASETS (Michihiro Kuramochi and George Karypis). 7 UNSUPERVISED AND SUPERVISED PATTERN LEARNING IN GRAPH DATA (Diane J. Cook, Lawrence B. Holder, and Nikhil Ketkar). 8 GRAPH GRAMMAR LEARNING (Istvan Jonyer). 9 CONSTRUCTING DECISION TREE BASED ON CHUNKINGLESS GRAPH-BASED INDUCTION (Kouzou Ohara, Phu Chien Nguyen, Akira Mogi, Hiroshi Motoda, and Takashi Washio). 10 SOME LINKS BETWEEN FORMAL CONCEPT ANALYSIS AND GRAPH MINING (Michel Liquière). 11 KERNEL METHODS FOR GRAPHS (Thomas Gärtner, Tamás Horváth, Quoc V. Le, Alex J. Smola, and Stefan Wrobel). 12 KERNELS AS LINK ANALYSIS MEASURES (Masashi Shimbo and Takahiko Ito). 13 ENTITY RESOLUTION IN GRAPHS (Indrajit Bhattacharya and Lise Getoor). Part III APPLICATIONS. 14 MINING FROM CHEMICAL GRAPHS (Takashi Okada). 15 UNIFIED APPROACH TO ROOTED TREE MINING: ALGORITHMS AND APPLICATIONS (Mohammed Zaki). 16 DENSE SUBGRAPH EXTRACTION (Andrew Tomkins and Ravi Kumar). 17 SOCIAL NETWORK ANALYSIS (Sherry E. Marcus, Melanie Moy, and Thayne Coffman). Index.

DIANE J. COOK, PhD, is the Huie-Rogers Chair Professor in the School of Electrical Engineering and Computer Science at Washington State University. Her extensive research in artificial intelligence and data mining has been supported by grants from the National Science Foundation, NASA, DARPA, and Texas Instruments. Dr. Cook is the coauthor of Smart Environments: Technology, Protocols, and Applications (Wiley). LAWRENCE B. HOLDER, PhD, is Professor in the School of Electrical Engineering and Computer Science at Washington State University, where he teaches and conducts research in artificial intelligence, machine learning, data mining, graph theory, parallel and distributed processing, and cognitive architectures.

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