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This book provides an example of the capitalization of computer and wiki technology to support collaborative writing among Mainland Chinese upper primary school students. It presents the results of a study showing the application of the Design-Based Research (DBR) methodology to design a Wiki-based Collaborative Process Writing Pedagogy (WCPWP) to help students with their writing in the Chinese context. The WCPWP is designed and developed based on social constructivist theory and the social view of writing process theory, as well as in consideration of the Technological, Pedagogical, and Content Knowledge (TPACK) framework.Primarily aimed at researchers and practitioners in the fields of collaborative learning, TPACK, and Chinese writing, as well as Chinese language educators, this book will also deepen primary educators'' understanding of the links among technology, pedagogy and content, and guide educators in the integration of social media, as well as the design of effective matching pedagogic strategies, in their teaching of writing.

What is data intelligence? How can data intelligence influence education system systematically? The paradigm shift of scientific research implies a coming age of data-driven educational research and practice. This book presents research and practice of data intelligence in education from three levels: (i) educational governance, (ii) teaching practice, and (iii) student learning. Each chapter gives an analysis of fundamental knowledge, key themes, the state-of-the-art technologies and education application cases. This interdisciplinary book is essential reading for anyone interested in applying big data technology in education and for different stakeholders including education administrators, teachers, students, and researchers to broaden their minds to wisely use educational data to solve complex problems in the education field.

Our collected work contains mathematics education research papers. Comparative studies of school textbooks cover content selection, compilation style, representation method, design of examples and exercises, mathematics investigation, the use of information technology, and composite difficulty level, to name a few.

Our collected work contains mathematics education research papers. Comparative studies of school textbooks cover content selection, compilation style, representation method, design of examples and exercises, mathematics investigation, the use of information technology, and composite difficulty level, to name a few.

This illustrative compendium analyzes the load balancing problem in distributed stream processing systems and explores a set of high-performance real-time processing scheme based on key-based balancing strategy, join-matrix model and fault tolerance mechanisms.The volume succinctly provides the theoretical support for the proposed techniques. Through a rich set of experiments and comparisons with the other state-of-the-art techniques using both standard benchmarks and real data sets, the book comprehensively verifies the correctness and effectiveness of the proposed methods.This unique title is an excellent reference text for researchers in the fields of distributed stream processing, parallel system, cloud computing, etc.

Conceived as a cross between natural language processing methods and biological sequences in DNA, RNA and protein, biological language model is a new scientific research topic in bioinformatics that has been extensively studied by the authors. The basic theory and applications of this model are presented in this book to serve as an reference for graduate students and researchers.

This unique compendium focuses on the acquisition and analysis of social media data. The approaches concern both the data-intensive characteristics and graphical structures of social media. The book addresses the critical problems in social media analysis, which representatively cover its lifecycle.The must-have volume is an excellent reference text for professionals, researchers, academics and graduate students in AI and databases.

This book is the first of its kind to treat high-frequency trading and technical analysis as accurate sciences.

As mobile devices continue becoming a larger part of our lives, the development of location acquisition technologies to track moving objects have focused the minds of researchers on issues ranging from longitude and latitude coordinates, speed, direction, and timestamping, as part of parameters needed to calculate the positional information and locations of objects, in terms of time and position in the form of trajectory streams. Recently, recent advances have facilitated various urban applications such as smart transportation and mobile delivery services.Unlike other books on spatial databases, mobile computing, data mining, or computing with spatial trajectories, this book is focused on smart transportation applications.This book is a good reference for advanced undergraduates, graduate students, researchers, and system developers working on transportation systems.

Transaction processing is fundamental for many modern applications. These applications require the backend transaction processing engines to be available at all times as well as provide a massive horizontal scale for intensive transaction requests.Concurrency Control and Recovery features recent progress in research in online transaction processing. The book also showcases the authors' research on a highly scalable OLTP system. Its contents include the designs of an efficient multiple version storage engine, a scalable range optimistic concurrency control, high-performance Paxos-based log replication, global snapshot isolation, and fast follower recovery.This book is written for professionals, researchers, and graduate students specialising in database systems and its related fields.

Online social networking sites like Facebook, LinkedIn, and Twitter, offer millions of members the opportunity to befriend one another, send messages to each other, and post content on the site - actions which generate mind-boggling amounts of data every day.To make sense of the massive data from these sites, we resort to social media mining to answer questions like the following: What are social communities in bipartite graphs and signed graphs? How robust are the networks? How can we apply the robustness of networks? How can we find identical social users across heterogeneous social networks?Social media shatters the boundaries between the real world and the virtual world. We can now integrate social theories with computational methods to study how individuals interact with each other and how social communities form in bipartite and signed networks. The uniqueness of social media data calls for novel data mining techniques that can effectively handle user generated content with rich social relations. The study and development of these new techniques are under the purview of social media mining, an emerging discipline under the umbrella of data mining. Social Media Mining is the process of representing, analyzing, and extracting actionable patterns from social media data.

This unique compendium provides a novel research on how time influences the conversions of advertising and product recommendation in E-commerce. It proposes time-aware conversion prediction models to solve the problem - what products should be recommended for a given period to maximize conversion? The volume also presents a series of researches on how to build data-driven attribution models to allocate the time-sensitive contribution of advertisements to the conversion. This must-have reference text will be invaluable for researchers, professionals, academics and graduate students keen in databases and artificial intelligence.

 Data analysis is of upmost importance in the mining of big data, where knowledge discovery and inference are the basis for intelligent systems to support the real world applications. However, the process involves knowledge acquisition, representation, inference and data, Bayesian network (BN) is the key technology plays a key role in knowledge representation, in order to pave way to cope with incomplete, fuzzy data to solve the real-life problems.This book presents Bayesian network as a technology to support data-intensive and incremental learning in knowledge discovery, inference and data fusion in uncertain environment.