Anti-Spam Techniques Based on Artificial Immune System - Tan, Ying
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This book introduces anti-spam techniques based on the artificial immune system (AIS). It discusses key topics in AIS-based anti-spam techniques, including extraction methods, construction approaches, classifiers based on immune danger theory, and the immune-based dynamic algorithm plus strategies for designing and applying spam-filtering models.

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Produktbeschreibung
This book introduces anti-spam techniques based on the artificial immune system (AIS). It discusses key topics in AIS-based anti-spam techniques, including extraction methods, construction approaches, classifiers based on immune danger theory, and the immune-based dynamic algorithm plus strategies for designing and applying spam-filtering models.
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Autorenporträt
Ying Tan, PhD, is a full professor and PhD advisor in the School of Electronics Engineering and Computer Science at Peking University, China. He is also director of the Computational Intelligence Laboratory at Peking University. He received his PhD from Southeast University in Nanjing, China. His research interests include computational intelligence, swarm intelligence, data mining, machine learning, fireworks algorithm, and intelligent information processing for information security. He has published more than 280 papers, has authored or coauthored six books and more than 10 book chapters, and holds three invention patents. He is editor in chief of the International Journal of Computational Intelligence and Pattern Recognition and is an associate editor of IEEE Transactions on Cybernetics and IEEE Transactions on Neural Networks and Learning Systems. He is the general chair of the ICSI-CCI 2015 joint conference and ICSI series conference and is a senior member of the IEEE.