Assuming no prior knowledge of mathematics or data mining, this self-contained book presents a "do-it-yourself" approach to extracting interesting patterns from graph data. Each chapter focuses on a graph mining task, such as link analysis, cluster analysis, and classification. Through many applications, the book demonstrates how computational techniques can help solve real-world problems. Every algorithm and example is accompanied with R code, allowing readers to see how the algorithmic techniques correspond to the process of graph data analysis and to use the graph mining techniques in practice.
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