Social Influence Based Clustering of Heterogeneous Information Networks thumbnail
slide-image
Pause
Mute
Subtitles not available
Playback speed
0.25
0.5
0.75
1
1.25
1.5
1.75
2
Full screen

Social Influence Based Clustering of Heterogeneous Information Networks

Published on Sep 27, 20134017 Views

Social networks continue to grow in size and the type of information hosted. We witness a growing interest in clustering a social network of people based on both their social relationships and their

Related categories

Chapter list

SI-Cluster: Social Influence Based Clustering of Heterogeneous Information Networks00:00
Social Influence00:13
Motivation00:36
Various InformationNetworks involved in SI-Cluster01:59
Activity Network and Influence Network02:45
Problem Definition03:44
Social Influence Propagate across Multiple Influence Networks06:00
Step 1: Reorganize a Heterogeneous Graph into Three Subgraphs06:30
Self-Influence Kernel on Social Graph08:08
Step 2: Compute Self-influence Similarity09:29
Co-influence Kernelon Influence Graph10:43
Step 3: Compute Propagating Co-influence Kernel on Influence Graph10:48
Step 4: Partition Activities into Clusters (area-based)12:14
Propagate Heat Distribution12:18
Step 5.1: Compute Influence Score Based on Co-influence Model13:04
Step 5.2: Classify People Using Influence Propagation13:24
Influence Scores of Authors Based on Conference and Keyword Partitions14:09
Step 6: Compute Co-influence Similarity15:19
Influence-based Similarity15:38
Step 7: Compute Unified Influence-based Similarity16:50
Clustering Objective Function17:08
Parameter-based Optimization18:03
Social Influence Based Graph Clustering20:19
Experimental Evaluation21:33
Cluster Quality Evaluation22:28
Clustering Efficiency22:43
Clustering Convergence23:13
Conclusions23:38
Thank you!24:22