Broad Learning Through Fusions
An Application on Social Networks
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ISBN-13:
9783030125271
Veröffentl:
2019
Einband:
HC runder Rücken kaschiert
Erscheinungsdatum:
28.06.2019
Seiten:
436
Autor:
Philip S. Yu
Gewicht:
1012 g
Format:
260x183x29 mm
Sprache:
Englisch
Beschreibung:
This book offers a clear and comprehensive introduction to broad learning, one of the novel learning problems studied in data mining and machine learning. Broad learning aims at fusing multiple large-scale information sources of diverse varieties together, and carrying out synergistic data mining tasks across these fused sources in one unified analytic. This book takes online social networks as an application example to introduce the latest alignment and knowledge discovery algorithms. Besides the overview of broad learning, machine learning and social network basics, specific topics covered in this book include network alignment, link prediction, community detection, information diffusion, viral marketing, and network embedding.
This book provides an introduction to broad learning, focusing on the fundamental concepts, learning tasks, and methodologies to build learning models for data fusion, and knowledge discovery.
1 Broad Learning Introduction.- 2 Machine Learning Overview.- 3 Social Network Overview.- 4 Supervised Network Alignment.- 5 Unsupervised Network Alignment.- 6 Semi-supervised Network Alignment.- 7 Link Prediction.- 8 Community Detection.- 9 Information Diffusion.- 10 Viral Marketing.- 11 Network Embedding.- 12 Frontier and Future Directions.- References.
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