Handbook of mobility data mining. Volume One, Data preprocessing and visualization /

"Handbook of Mobility Data Mining, Volume One: Data Preprocessing and Visualization introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book expl...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Zhang, Haoran (College teacher) (Editor)
Format: eBook
Language:English
Published: Amsterdam, Netherlands ; Cambridge, MA : Elsevier, [2023]
Subjects:
Online Access:Connect to the full text of this electronic book

MARC

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245 0 0 |a Handbook of mobility data mining.  |n Volume One,  |p Data preprocessing and visualization /  |c edited by Haoran Zhang. 
246 3 0 |a Data preprocessing and visualization 
264 1 |a Amsterdam, Netherlands ;  |a Cambridge, MA :  |b Elsevier,  |c [2023] 
264 4 |c ©2023 
300 |a 1 online resource :  |b illustrations (some color) 
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505 0 |a Chapter One - An overview of urban data variety and respective value to urban computing -- Chapter Two - Quality assessment for big mobility data -- Chapter Three - Noise filter method for mobile trajectory data -- Chapter Four - Modifiable areal unit problem in grided population density map -- Chapter Five - Few-shot count estimation of mobility dynamics by scaling GPS -- Chapter Six - Trip segmentation and mode detection for human mobility data -- Chapter Seven - Benchmark of travel mode detection with smartphone GPS trajectories -- Chapter Nine - Map-matching for low accuracy trajectory data -- Chapter Ten - Social information labeling for individual mobile phone user -- Chapter eleven - Web-based spatio-temporal data visualization technology for urban digital twin. 
504 |a Includes bibliographical references and index. 
520 |a "Handbook of Mobility Data Mining, Volume One: Data Preprocessing and Visualization introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. The book contains crucial information for researchers, engineers, operators, administrators, and policymakers seeking greater understanding of current technologies' infra-knowledge structure and limitations."--Provided by Publisher. 
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