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Link Mining: Models, Algorithms, and Applications

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Cover of 'Link Mining: Models, Algorithms, and Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Machine Learning Approaches to Link-Based Clustering
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    Chapter 2 Scalable Link-Based Similarity Computation and Clustering
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    Chapter 3 Community Evolution and Change Point Detection in Time-Evolving Graphs
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    Chapter 4 A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks
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    Chapter 5 Markov Logic: A Language and Algorithms for Link Mining
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    Chapter 6 Understanding Group Structures and Properties in Social Media
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    Chapter 7 Time Sensitive Ranking with Application to Publication Search
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    Chapter 8 Proximity Tracking on Dynamic Bipartite Graphs: Problem Definitions and Fast Solutions
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    Chapter 9 Discriminative Frequent Pattern-Based Graph Classification
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    Chapter 10 Information Integration for Graph Databases
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    Chapter 11 Veracity Analysis and Object Distinction
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    Chapter 12 Dynamic Community Identification
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    Chapter 13 Structure and Evolution of Online Social Networks
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    Chapter 14 Toward Identity Anonymization in Social Networks
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    Chapter 15 Interactive Graph Summarization
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    Chapter 16 InfoNetOLAP: OLAP and Mining of Information Networks
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    Chapter 17 Integrating Clustering with Ranking in Heterogeneous Information Networks Analysis
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    Chapter 18 Mining Large Information Networks by Graph Summarization
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    Chapter 19 Finding High-Order Correlations in High-Dimensional Biological Data
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    Chapter 20 Functional Influence-Based Approach to Identify Overlapping Modules in Biological Networks
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    Chapter 21 Gene Reachability Using Page Ranking on Gene Co-expression Networks
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