Computational Structural Behavior / by Cheng Wang.

Format:

Book

Author/Creator:

Wang, Cheng.

Series:

Computer Science Series

Language:

English

Subjects (All):

Data mining.

Artificial intelligence--Data processing.

Artificial intelligence.

Data Mining and Knowledge Discovery.

Data Science.

Local Subjects:

Data Mining and Knowledge Discovery.

Data Science.

Physical Description:

1 online resource (324 pages)

Edition:

1st ed. 2026.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2026.

Summary:

As intelligent behavior modeling grows increasingly complex, existing models have reached a bottleneck in their ability to express behavior. This book proposed the concept—Behavioral Molecular Structure—to redefine behavior representation from a structural perspective, paving the way for an entirely new research paradigm: Computational Structural Behavior. Addressing cutting-edge applications in behavior analysis, modeling, and prediction, this book explores how behavioral molecular structures can enhance the expressive power of intelligent models in handling complex behavioral data. It covers key topics such as behavioral space definition, molecular structure construction, representation learning, and downstream task integration, demonstrating their impact through real-world applications in fraud detection, behavior prediction, anomaly detection, and behavior generation. Suitable for researchers, engineers, and professionals in computer science, artificial intelligence, and behavioral studies, this book bridges the gap between theory and practice, offering a novel approach to improving behavior modeling. Whether you’re seeking innovative methodologies to enhance intelligent systems or exploring new frontiers in behavioral research, this book provides essential insights and practical guidance.

Contents:

Chapter 1. Overview of Computational Structural Behavior

Chapter 2. Enhancing Behavior Expression through Behavioral Structure

Chapter 3. Behavior Molecule-level Learning by Behavioral Interior Reconstruction

Chapter 4. Behavior Molecule-level Learning on Fine-grained Attribute Structure

Chapter 5. Improving Behavioral Data by Behavioral Molecule Generation

Chapter 6. Identifying Hidden Cybercrime Behavior by Behavior Tomographer

Chapter 7. Predicting Extraordinary Behavior Sequence by Spatiotemporal Transformer

Chapter 8. Detecting Evolving Behavior in Open World.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

9789819510139

OCLC:

1559219776