Yu P.S., Jiawei Han, Faloutsos C. (eds.) Link mining: Models, algorithms, and applications

New York: Springer, 2010. — 600 p.With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on "flat" or “isolated” data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links. Hence, the study of link mining will have a high impact on various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics. Link Mining: Models, Algorithms, and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view. Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people's daily lives call for exploring the techniques of mining linkage data. This book provides comprehensive coverage of the link mining models, techniques, and applications. Each chapter is contributed by some well-known researchers in the field. Link Mining: Models, Algorithms, and Applications is designed for researchers, teachers, and advanced-level students in computer science. This book is also suitable for practitioners in industry.Machine Learning Approaches to Link-Based Clustering.
Scalable Link-Based Similarity Computation and Clustering.
Community Evolution and Change Point Detection in Time-Evolving Graphs.A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks.
Markov Logic: A Language and Algorithms for Link Mining.
Understanding Group Structures and Properties in Social Media.
Time Sensitive Ranking with Application to Publication Search.
Proximity Tracking on Dynamic Bipartite Graphs: Problem Definitions and Fast Solutions.
Discriminative Frequent Pattern-Based Graph Classification.Information Integration for Graph Databases.
Veracity Analysis and Object Distinction.Dynamic Community Identification.
Structure and Evolution of Online Social Networks.
Toward Identity Anonymization in Social Networks.Interactive Graph Summarization.
InfoNetOLAP: OLAP and Mining of Information Networks.
Integrating Clustering with Ranking in Heterogeneous Information Networks Analysis.
Mining Large Information Networks by Graph Summarization.Finding High-Order Correlations in High-Dimensional Biological Data.
Functional Influence-Based Approach to Identify Overlapping Modules in Biological Networks.Gene Reachability Using Page Ranking on Gene Co-expression Networks.