Broad Learning Through Fusions An Application on Social Networks /

• Main Authors: Zhang, Jiawei (Author, http://id.loc.gov/vocabulary/relators/aut), Yu, Philip S. (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Subjects: Data mining.; Artificial intelligence.; Data structures (Computer science).; Application software.; Mathematical statistics.; Data Mining and Knowledge Discovery.; Artificial Intelligence.; Data Structures.; Information Systems Applications (incl. Internet).; Probability and Statistics in Computer Science.

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 ta...

Table of Contents:

• 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.