East China Normal University Scientific Reports – serie

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.

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.

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.

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 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.

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.

This book introduces the Design-Based Research (DBR) methodology to develop a pedagogy named Wiki-based Collaborative Process Writing Pedagogy (WCPWP). Through this, teachers can enrich their teaching knowledge and orchestrate collaborative writing activities by using Wiki to help primary school students with their Chinese writing.The results of this study have theoretical implications for applying Technological, Pedagogical, and Content Knowledge (TPACK) framework and design principles for implementing Wiki-based collaborative process writing in the Chinese context. It is an example of capitalizing on computer and Wiki technologies to support collaborative writing among upper primary school students in Mainland China.

Professor Xihua Cao (1920–2005) was a leading scholar at East China Normal University (ECNU) and a famous algebraist in China. His contribution to the Chinese academic circle is particularly the formation of a world-renowned "ECNU School" in algebra, covering research areas include algebraic groups, quantum groups, algebraic geometry, Lie algebra, algebraic number theory, representation theory and other hot fields. In January 2020, in order to commemorate Professor Xihua Cao's centenary birthday, East China Normal University held a three-day academic conference. Scholars at home and abroad gave dedications or delivered lectures in the conference. This volume originates from the memorial conference, collecting the dedications of scholars, reminiscences of family members, and 16 academic articles written based on the lectures in the conference, covering a wide range of research hot topics in algebra. The book shows not only scholars' respect and memory for Professor Xihua Cao, but also the research achievements of Chinese scholars at home and abroad.

Technology transfer studies are usually framed through Economics and Management Sciences, but this volume Geography of Technology Transfer in China seeks to reveal the mechanism of technology transfer from the geographical perspective. It not only depicts the spatial evolution laws of glocal technology transfer networks, but also uses regression models to uncover the two-way effects between the networks and innovative capacity. In addition, this book highlights the integration and interaction of networks on both the global and local scales. A theoretical framework on glocal networks of technology transfer is established based on a series of economic geography bases in order to depict the spatial differences and coupling mechanism among multi-scaled networks in China.This book consists of 5 parts and 10 chapters, which illustrate the background, theoretical basis, spatial evolution, dual-way influences, and policy implications of technology transfer in China, presenting a clear structure both theoretically and empirically. The book begins with the "what", "why", and "how" questions behind geographical studies on technology transfer to clarify the purpose of the book and its differentiation from present technology transfer studies. Thereafter, it discusses the "holy trinity" framework of glocal technology transfer networks consisting of cultural, territorial, and networked subsystems. To this end, the spatial evolution of the technology transfer is highlighted through soical network analysis, which aims at depicting the geographical rules of China's technology transfer networks at global, domestic, and regional scales. Based on these discoveries, the next part of the book further analyzes, through a series of regression models such as ERGM and NBRM, the kinds of determinants which have influenced the network size and how the network has in turn affected local innovation capacity . Lastly, the policy implications connect the findings of empirical studies with the operability of the national innovation system. On the whole, this book extensively covers the theoretical, empirical, and practical applications of the geography of technology transfer in China.

Roads are essential components of a city. Despite their increasing importance in our daily lives, modeling and simulating road networks is challenging due to their dynamic and complex nature. The underlying order and patterns of the seemingly chaotic and diverse physical patterns of roads are still unclear. Furthermore, there is a knowledge gap regarding the relationships between the size, scale, shape, structure, and space of road networks.This book presents the state-of-the-art in computational methods for modeling the topological structure of road networks. Each chapter focuses on a specific aspect of this topology and provides models, indicators, and empirical studies of road network structures. The book includes six types of structural models and three types of spatial simulation models to help understand the topological structural complexity of road networks. The appendices include several examples of road networks and their universal scale-free patterns.This interdisciplinary book is helpful for individuals interested in spatial modeling, network analysis, transportation geography, and urban studies. It is also a fundamental resource for modeling and computing spatial complex systems. The book is suitable for undergraduate, graduate, and professional researchers interested in geographic modeling and urban design. The text is written with moderate mathematical detail to enhance comprehension of the concepts and principles presented. The use of maps, graphics, and examples makes the modeling and computational processes more intuitive.

This book presents the recent achievements on the processing of representative user generated content (UGC) on E-commerce websites. This large size of UGC is valuable information for data mining to help customer/object profiling. It provides a comprehensive overview on the concept of customer credibility, object-oriented review summarization technology and content-based collaborative filtering algorithm. It covers a feedback mechanism which is designed to discover customer credibility, which is used to define the professional degree of review content; product-oriented review summarization for restaurants or trip arrangements, and introduced content-based collaborative filtering for product recommendation.

This book presents the recent achievements on the processing of representative user generated content (UGC) on E-commerce websites. This large size of UGC is valuable information for data mining to help customer/object profiling. It provides a comprehensive overview on the concept of customer credibility, object-oriented review summarization technology and content-based collaborative filtering algorithm. It covers a feedback mechanism which is designed to discover customer credibility, which is used to define the professional degree of review content; product-oriented review summarization for restaurants or trip arrangements, and introduced content-based collaborative filtering for product recommendation.

This book provides a comprehensive introduction on opinion analysis for online reviews. It offers the newest research on opinion mining, including theories, algorithms and datasets. A new feature presentation method is highlighted for sentiment classification. Then, a three-phase framework for sentiment classification is proposed, where a set of sentiment classifiers are selected automatically to make predictions. Such predictions are integrated via ensemble learning. Finally, to solve the problem of combination explosion encountered, a greedy algorithm is devised to select the base classifiers.

This book provides a comprehensive introduction on opinion analysis for online reviews. It offers the newest research on opinion mining, including theories, algorithms and datasets. A new feature presentation method is highlighted for sentiment classification. Then, a three-phase framework for sentiment classification is proposed, where a set of sentiment classifiers are selected automatically to make predictions. Such predictions are integrated via ensemble learning. Finally, to solve the problem of combination explosion encountered, a greedy algorithm is devised to select the base classifiers.

Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams cannot be applied to deal with data uncertainty directly due to the exponential growth of possible solution space.This book provides a comprehensive overview of the authors' work on querying and mining uncertain data streams. Its contents include some important discoveries dealing with typical topics such as top-k query, ER-Topk query, rarity estimation, set similarity, and clustering.Querying and Mining Uncertain Data Streams is written for professionals, researchers, and graduate students in data mining and its various related fields.

Data uncertainty widely exists in many applications, and an uncertain data stream is a series of uncertain tuples that arrive rapidly. However, traditional techniques for deterministic data streams cannot be applied to deal with data uncertainty directly due to the exponential growth of possible solution space.This book provides a comprehensive overview of the authors' work on querying and mining uncertain data streams. Its contents include some important discoveries dealing with typical topics such as top-k query, ER-Topk query, rarity estimation, set similarity, and clustering.Querying and Mining Uncertain Data Streams is written for professionals, researchers, and graduate students in data mining and its various related fields.

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.

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.Related Link(s);

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.

This book is the first of its kind to treat high-frequency trading and technical analysis as accurate sciences. The authors reveal how to build trading algorithms of high-frequency trading and obtain stable statistical arbitrage from the financial market in detail. The authors' arguments are based on rigorous mathematical and statistical deductions and this will appeal to people who believe in the theoretical aspect of the topic.Investors who believe in technical analysis will find out how to verify the efficiency of their technical arguments by ergodic theory of stationary stochastic processes, which form a mathematical background for technical analysis. The authors also discuss technical details of the IT system design for high-frequency trading.

This book is the first of its kind to treat high-frequency trading and technical analysis as accurate sciences. The authors reveal how to build trading algorithms of high-frequency trading and obtain stable statistical arbitrage from the financial market in detail. The authors' arguments are based on rigorous mathematical and statistical deductions and this will appeal to people who believe in the theoretical aspect of the topic.Investors who believe in technical analysis will find out how to verify the efficiency of their technical arguments by ergodic theory of stationary stochastic processes, which form a mathematical background for technical analysis. The authors also discuss technical details of the IT system design for high-frequency trading.

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. Other papers included are about representation of basic mathematical thought in school textbooks, a study on the compilation features of elementary school textbooks, and a survey of the effect of using new elementary school textbooks.

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. Other papers included are about representation of basic mathematical thought in school textbooks, a study on the compilation features of elementary school textbooks, and a survey of the effect of using new elementary school textbooks.