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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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Title
Link Mining: Models, Algorithms, and Applications
Published by
Springer New York, January 2010
DOI 10.1007/978-1-4419-6515-8
ISBNs
978-1-4419-6514-1, 978-1-4419-6515-8, 978-1-4939-0147-0
Editors

Philip S. Yu, Jiawei Han, Christos Faloutsos

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 197 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 10 5%
China 5 3%
Germany 3 2%
Brazil 2 1%
Korea, Republic of 2 1%
United Kingdom 2 1%
Canada 2 1%
Australia 1 <1%
Singapore 1 <1%
Other 6 3%
Unknown 163 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 70 36%
Student > Master 28 14%
Researcher 24 12%
Professor > Associate Professor 14 7%
Student > Bachelor 11 6%
Other 32 16%
Unknown 18 9%
Readers by discipline Count As %
Computer Science 123 62%
Business, Management and Accounting 11 6%
Engineering 9 5%
Social Sciences 8 4%
Agricultural and Biological Sciences 6 3%
Other 17 9%
Unknown 23 12%