Clustering And Outlier Detection For Trajectory Stream Data
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Clustering And Outlier Detection For Trajectory Stream Data
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Author : Jiali Mao
language : en
Publisher: World Scientific
Release Date : 2020-02-18
Clustering And Outlier Detection For Trajectory Stream Data written by Jiali Mao and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-18 with Computers categories.
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.
Clustering And Outlier Detection For Trajectory Stream Data
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Author : Cheqing Jin
language : en
Publisher: East China Normal University S
Release Date : 2020
Clustering And Outlier Detection For Trajectory Stream Data written by Cheqing Jin and has been published by East China Normal University S this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Database management categories.
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.
Outlier Detection For Temporal Data
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Author : Manish Gupta
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Outlier Detection For Temporal Data written by Manish Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book. A large number of applications generate temporal datasets. For example, in our everyday life, various kinds of records like credit, personnel, financial, judicial, medical, etc., are all temporal. This stresses the need for an organized and detailed study of outliers with respect to such temporal data. In the past decade, there has been a lot of research on various forms of temporal data including consecutive data snapshots, series of data snapshots and data streams. Besides the initial work on time series, researchers have focused on rich forms of data including multiple data streams, spatio-temporal data, network data, community distribution data, etc. Compared to general outlier detection, techniques for temporal outlier detection are very different. In this book, we will present an organized picture of both recent and past research in temporal outlier detection. We start with the basics and then ramp up the reader to the main ideas in state-of-the-art outlier detection techniques. We motivate the importance of temporal outlier detection and brief the challenges beyond usual outlier detection. Then, we list down a taxonomy of proposed techniques for temporal outlier detection. Such techniques broadly include statistical techniques (like AR models, Markov models, histograms, neural networks), distance- and density-based approaches, grouping-based approaches (clustering, community detection), network-based approaches, and spatio-temporal outlier detection approaches. We summarize by presenting a wide collection of applications where temporal outlier detection techniques have been applied to discover interesting outliers. Table of Contents: Preface / Acknowledgments / Figure Credits / Introduction and Challenges / Outlier Detection for Time Series and Data Sequences / Outlier Detection for Data Streams / Outlier Detection for Distributed Data Streams / Outlier Detection for Spatio-Temporal Data / Outlier Detection for Temporal Network Data / Applications of Outlier Detection for Temporal Data / Conclusions and Research Directions / Bibliography / Authors' Biographies
Emerging Trends Techniques And Applications In Geospatial Data Science
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Author : Gaur, Loveleen
language : en
Publisher: IGI Global
Release Date : 2023-04-24
Emerging Trends Techniques And Applications In Geospatial Data Science written by Gaur, Loveleen and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-24 with Technology & Engineering categories.
With the emergence of smart technology and automated systems in today’s world, big data is being incorporated into many applications. Trends in data can be detected and objects can be tracked based on the real-time data that is utilized in everyday life. These connected sensor devices and objects will provide a large amount of data that is to be analyzed quickly, as it can accelerate the transformation of smart technology. The accuracy of prediction of artificial intelligence (AI) systems is drastically increasing by using machine learning and other probability and statistical approaches. Big data and geospatial data help to solve complex issues and play a vital role in future applications. Emerging Trends, Techniques, and Applications in Geospatial Data Science provides an overview of the basic concepts of data science, related tools and technologies, and algorithms for managing the relevant challenges in real-time application domains. The book covers a detailed description for readers with practical ideas using AI, the internet of things (IoT), and machine learning to deal with the analysis, modeling, and predictions from big data. Covering topics such as field spectra, high-resolution sensing imagery, and spatiotemporal data engineering, this premier reference source is an excellent resource for data scientists, computer and IT professionals, managers, mathematicians and statisticians, health professionals, technology developers, students and educators of higher education, librarians, researchers, and academicians.
Outlier Detection For Temporal Data
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Author : Manish Gupta
language : en
Publisher:
Release Date : 2014-03
Outlier Detection For Temporal Data written by Manish Gupta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03 with Outliers (Statistics) categories.
Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book. A large number of applications generate temporal datasets. For example, in our everyday life, various kinds of records like credit, personnel, financial, judicial, medical, etc., are all temporal. This stresses the need for an organized and detailed study of outliers with respect to such temporal data. In the past decade, there has been a lot of research on various forms of temporal data including consecutive data snapshots, series of data snapshots and data streams. Besides the initial work on time series, researchers have focused on rich forms of data including multiple data streams, spatio-temporal data, network data, community distribution data, etc. Compared to general outlier detection, techniques for temporal outlier detection are very different. In this book, we will present an organized picture of both recent and past research in temporal outlier detection. We start with the basics and then ramp up the reader to the main ideas in state-of-the-art outlier detection techniques. We motivate the importance of temporal outlier detection and brief the challenges beyond usual outlier detection. Then, we list down a taxonomy of proposed techniques for temporal outlier detection. Such techniques broadly include statistical techniques (like AR models, Markov models, histograms, neural networks), distance- and density-based approaches, grouping-based approaches (clustering, community detection), network-based approaches, and spatio-temporal outlier detection approaches. We summarize by presenting a wide collection of applications where temporal outlier detection techniques have been applied to discover interesting outliers.
Probabilistic Approaches For Social Media Analysis Data Community And Influence
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Author : Kun Yue
language : en
Publisher: World Scientific
Release Date : 2020-02-24
Probabilistic Approaches For Social Media Analysis Data Community And Influence written by Kun Yue and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-24 with Computers categories.
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.
School Mathematics Textbooks In China Comparative Studies And Beyond
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Author : Jianpan Wang
language : en
Publisher: World Scientific
Release Date : 2021-01-28
School Mathematics Textbooks In China Comparative Studies And Beyond written by Jianpan Wang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-28 with Mathematics categories.
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.
Geography Of Technology Transfer In China A Glocal Network Approach
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Author : Chengliang Liu
language : en
Publisher: World Scientific
Release Date : 2023-12-06
Geography Of Technology Transfer In China A Glocal Network Approach written by Chengliang Liu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-06 with Business & Economics categories.
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.
Proceedings Of Fifth International Conference On Computer And Communication Technologies
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Author : B. Rama Devi
language : en
Publisher: Springer Nature
Release Date :
Proceedings Of Fifth International Conference On Computer And Communication Technologies written by B. Rama Devi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Achieving Greater Educational Impact Through Data Intelligence Practice Challenges And Expectations Of Education
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Author : Bian Wu
language : en
Publisher: World Scientific
Release Date : 2021-11-24
Achieving Greater Educational Impact Through Data Intelligence Practice Challenges And Expectations Of Education written by Bian Wu and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-24 with Education categories.
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.