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Managing and Mining Graph Data
Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.
Graph Mining
What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are ...
Advances in Artificial Life
This book constitutes the refereed proceedings of the 9th European Conference on Artificial Life, ECAL 2007, held in Lisbon, Portugal. The 125 revised full papers cover morphogenesis and development, robotics and autonomous agents, evolutionary computation and theory, cellular automata, models of biological systems and their applications, ant colony and swarm systems, evolution of communication, simulation of social interactions, self-replication, artificial chemistry.
Complex Networks & Their Applications IX
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the IX International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2020). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks and technological networks.
Complex Networks and Their Applications VIII
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the Eighth International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2019), which took place in Lisbon, Portugal, on December 10–12, 2019. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, and network dynamics; diffusion, epidemics, and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.
Web Dynamics
The World Wide Web has become a ubiquitous global tool, used for finding infor mation, communicating ideas, carrying out distributed computation and conducting business, learning and science. The Web is highly dynamic in both the content and quantity of the information that it encompasses. In order to fully exploit its enormous potential as a global repository of information, we need to understand how its size, topology and content are evolv ing. This then allows the development of new techniques for locating and retrieving information that are better able to adapt and scale to its change and growth. The Web's users are highly diverse and can access the Web from a variety of devices and inte...
Nonequilibrium Statistical Mechanics in One Dimension
Self-contained and up-to-date guide to one-dimensional reactions, dynamics, diffusion and adsorption.
Our Self-Organized Brains
This book describes the dynamic nature of the brain and its mechanisms to develop cognitive skills, specifically learning. It will facilitate the reader’s appreciation and understanding of many concepts linked to cognition using a systemic approach to neuroscience. It introduces concepts of feedback control systems and self-organized systems that allow brain dynamics to be approached systemically, facilitating a holistic comprehension. The book is written in plain language and uses a wide variety of examples to facilitate its reading and understanding. It will serve to promote transdisciplinary communication in readers interested in the study of the fundamental dynamic aspects involved in the human learning process, both individually and socially.
Complexity in Language
This book is about dynamical, social-interactional aspects of the emergence of complexity in language, explained by linguists, cognitivists, and modelers.
Machine Learning, Optimization, and Data Science
This two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
