This book constitutes the thoroughly refereed post-proceedings of three workshops and an industrial track held in conjunction with the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China in May 2007. The 62 revised full papers presented together with an overview article to each workshop were carefully reviewed and selected from 355 submissions.

"This book provides the most recent technical information related to the computational models of the text mining process, discussing techniques within the realms of classification, association analysis, information extraction, and clustering. Offering an innovative approach to the utilization of textual information mining to maximize competitive advantage, it will provide libraries with the defining reference on this topic"--Provided by publisher.

The book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23–25, 2018. It comprises high-quality research by academics and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, case studies related to all the areas of data mining, machine learning, IoT and information security.

This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers and case studies related to all the areas of data mining, machine learning, Internet of things (IoT) and information security.

This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2022) held at Institute of Engineering & Management, Kolkata, India, during 23–25 February 2022. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT) and information security.

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains introduces the reader to recent research activities in the field of data mining. This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, while promoting understanding and implementation of data mining techniques in emerging domains.

"This book covers industrial databases and applications and offers generic database modeling techniques"--Provided by publisher.

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.

Bridging the gap between instructional design (ID) theory and practice in today's technology-enhanced learning environments, the book extends the current understanding of instructional science with an up-to-date perspective on emerging technologies and their affordances for teaching and learning. Positioning ID as a systematic process informed by theoretical assumptions, empirical evidence, and pragmatic considerations, this book provides an in-depth description and reflective analysis of good practice in technology-enhanced learning and design with a tripartite framework of pedagogy, technology, and evidence. It covers well-established ID theories and models with real-life examples of their effective integration with technological innovations. The book aims to advance the understanding of ID from both pedagogical and technological perspectives to improve educational practice and theory development in the information age. The book will be of interest to students and academics in educational technology, instructional science, and instructional design, as well as instructional designers and teachers.

"This book offers historical perspectives on mobile computing, as well as new frameworks and methodologies for mobile networks, intelligent mobile applications, and mobile computing applications"--Provided by publisher.