| Broad Learning Through Fusions: An Application on Social Networks 2019 Edition Contributor(s): Zhang, Jiawei (Author), Yu, Philip S. (Author) |
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ISBN: 3030125300 ISBN-13: 9783030125301 Publisher: Springer OUR PRICE: $52.24 Product Type: Paperback - Other Formats Published: August 2020 |
| Additional Information |
| BISAC Categories: - Computers | Databases - Data Mining - Computers | Data Modeling & Design - Computers | Information Technology |
| Dewey: 005.55 |
| Physical Information: 0.89" H x 7" W x 10" (1.66 lbs) 419 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |