Geocomputation, Sustainability And Environmental Planning

In an effort to improve various aspects of work-related communication, this work applies sophisticated machine learning techniques to a large body of email data..Modeling Intention in Email Several effective models are proposed that can aid with the prioritization of incoming messages, help with coordination of shared tasks, improve tracking of deadlines, and prevent disastrous information leaks.

This book presents up-to-date research approaches for developing technology-enhanced systems and tools to support functional online collaborative learning and work settings.Technology-Enhanced Systems and Tools for Collaborative Learning Scaffolding is a major research theme in CSCL and CSCW research community. It comprises a variety of research topics that span from the study of frameworks and infrastructures that foster collaborative learning and work through the application of different methods (distributed e-learning repositories, content creation and customization, social networks, collaborative ontologies building, and educational games) to the use of personalization and adaptation techniques to support the development of more powerful e-collaboration settings, including methodologies and tools for analyzing students' interactions with the aim to increase students' collaborative behaviors, performance and group organization.

It presents a comprehensive view of reasoning in event-based distributed systems, bringing together reviews of the state-of-the art, new research contributions, and an extensive set of references. Reasoning in Event-Based Distributed Systems Many different architectures, languages and technologies are being used for implementing event-based distributed systems, and much of the development has been undertaken independently by different communities.

 This book provides a specific introduction to data fusion problems using support vector machines. The topics presented in this book are meant for researchers or students who use support vector machines.Kernel-based Data Fusion for Machine Learning Data fusion problems arise frequently in many different fields.

  In the first part, this book begins with a brief survey of additive models and Rayleigh quotient objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem.  This book provides a specific introduction to data fusion problems using support vector machines.