
E-Commerce Big Data Mining and Analytics
Jie Cao(Author)
Springer (Publisher)
Published on 31. July 2024
Book
Paperback/Softback
XVII, 203 pages
978-981-99-3590-1 (ISBN)
Description
This book seeks to give readers with a preliminary but critical introduction and summary of e-commerce and big data analysis. This book introduces how to achieve data acquisition and pre-processing. Specifically, this book provides three representative and interesting scenarios to demonstrate the application of e-commerce and big data analysis, i.e., trajectory big data mining technology, e-commerce fraud and anti-fraud, and recommendation system. Also this book provides the basic and illustrative operation steps of python programming language for e-commerce and big data analysis. By reading this book, readers can learn the basic concepts and principles of e-commerce and big data analysis.
More details
Series
Edition
2023 ed.
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
Illustrations
21 s/w Abbildungen, 31 farbige Abbildungen
XVII, 203 p. 52 illus., 31 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 13 mm
Weight
347 gr
ISBN-13
978-981-99-3590-1 (9789819935901)
DOI
10.1007/978-981-99-3588-8
Schweitzer Classification
Other editions
Additional editions

Book
07/2023
Springer
€69.54
Shipment within 3-4 weeks
Person
Jie Cao, born in 1969, received his Ph.D. degree in engineering from South-east University in 2002, Ph.D. supervisor, part-time doctoral supervisor of Nan-jing University of Science and Technology and Hohai University. He has pub-lished more than 100 papers in TKDE, TPDS, TKDD, TWeb, TCyb, TNNLS, TII, TIST, InfSci, KDD, ICDM and other domestic and international journals and con-ferences, and the total number of citations exceeds 5,000, among which more than 100 are indexed by SCI. He was appointed as an editorial board member of Neu-rocomputing and World Wide Web Journal.
Content
Introduction to e-commerce big data mining and analytics.- Acquisition and preprocessing of e-commerce big data.- E-commerce trajectory big data mining technology.- Fraud and anti-fraud on e-commerce platform.- Design of recommendation system on e-commerce platform.- Case study.