Diane J. Cook – författare

This text takes a focused and comprehensive look at mining data represented as a graph, with the latest findings and applications in both theory and practice provided. Even if you have minimal background in analyzing graph data, with this book you’ll be able to represent data as graphs, extract patterns and concepts from the data, and apply the methodologies presented in the text to real datasets. There is a misprint with the link to the accompanying Web page for this book. For those readers who would like to experiment with the techniques found in this book or test their own ideas on graph data, the Web page for the book should be http://www.eecs.wsu.edu/MGD.

Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the fieldActivity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data. Each chapter is constructed to provide practical, step-by-step information on how to analyze and process sensor data. The book discusses techniques for activity learning that include the following: Discovering activity patterns that emerge from behavior-based sensor dataRecognizing occurrences of predefined or discovered activities in real timePredicting the occurrences of activitiesThe techniques covered can be applied to numerous fields, including security, telecommunications, healthcare, smart grids, and home automation. An online companion site enables readers to experiment with the techniques described in the book, and to adapt or enhance the techniques for their own use.With an emphasis on computational approaches, Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data provides graduate students and researchers with an algorithmic perspective to activity learning.

This book brings together research articles by active practitioners and leading researchers reporting recent advances in the field of knowledge discovery. An overview of the field, looking at the issues and challenges involved is followed by coverage of recent trends in data mining. This provides the context for the subsequent chapters on methods and applications. Part I is devoted to the foundations of mining different types of complex data like trees, graphs, links and sequences. A knowledge discovery approach based on problem decomposition is also described. Part II presents important applications of advanced mining techniques to data in unconventional and complex domains, such as life sciences, world-wide web, image databases, cyber security and sensor networks. With a good balance of introductory material on the knowledge discovery process, advanced issues and state-of-the-art tools and techniques, this book will be useful to students at Masters and PhD level in Computer Science, as well as practitioners in the field.

This book brings together research articles by active practitioners & leading researchers reporting recent advances in the field of knowledge discovery. An overview of the field, looking at the issues & challenges involved is followed by coverage of recent trends in data mining. This provides the context for the subsequent chapters on methods & applications. Part I is devoted to the foundations of mining different types of complex data like trees, graphs, links & sequences. A knowledge discovery approach based on problem decomposition is also described. Part II presents important applications of advanced mining techniques to data in unconventional & complex domains, such as life sciences, world-wide web, image databases, cyber security & sensor networks. With a good balance of introductory material on the knowledge discovery process, advanced issues & state-of-the-art tools & techniques, this book will be useful to students at Masters & PhD level in Computer Science, as well as practitioners in the field.

This book constitutes the proceedings of the 6th International Workshop on Human Behavior Understanding, HBU 2015, held in Osaka, Japan, in September 2015. The 11 full papers were carefully reviewed and selected from 15 initial submissions.