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Data Science and Digital Business

Overview of attention for book
Cover of 'Data Science and Digital Business'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Data Management and Visualization Using Big Data Analytics
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    Chapter 2 Data Science and Digital Business
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    Chapter 3 Data Science and Conversational Interfaces: A New Revolution in Digital Business
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    Chapter 4 After 2017: Managers Exit and Banks Arise
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    Chapter 5 Synergies Between Association Rules and Collaborative Filtering in Recommender System: An Application to Auto Industry
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    Chapter 6 Information Security Research Challenges in the Process of Digitizing Business: A Review Based on the Information Security Model of IBM
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    Chapter 7 Deploying a Scalable Data Science Environment Using Docker
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    Chapter 8 Clean up CHAOS and Use E-CRM (A Digital Concept) to Expand the Business: A Case of Pakistan
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    Chapter 9 Furthering Big Data Utilization in Tourism
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    Chapter 10 C-LASSO Estimator for Generalized Additive Logistic Regression Based on B-Spline
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    Chapter 11 An Efficient Bundle-Like Algorithm for Data-Driven Multi-objective Bi-level Signal Design for Traffic Networks with Hazardous Material Transportation
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    Chapter 12 Advanced Regression Models: Least Squares, Nonlinear, Poisson and Binary Logistics Regression Using R
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    Chapter 13 Student Desertion: What Is and How Can It Be Detected on Time?
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    Chapter 14 Bioelectric Potential Plant
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    Chapter 15 False Alarms Management by Data Science
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    Chapter 16 Introduction to Data Science and Digital Business
Attention for Chapter 13: Student Desertion: What Is and How Can It Be Detected on Time?
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Citations

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32 Mendeley
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Chapter title
Student Desertion: What Is and How Can It Be Detected on Time?
Chapter number 13
Book title
Data Science and Digital Business
Published by
Springer, Cham, January 2019
DOI 10.1007/978-3-319-95651-0_13
Book ISBNs
978-3-31-995650-3, 978-3-31-995651-0
Authors

Jonathan Vásquez, Jaime Miranda, Vásquez, Jonathan, Miranda, Jaime

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Professor 4 13%
Student > Master 4 13%
Student > Bachelor 3 9%
Researcher 3 9%
Student > Ph. D. Student 2 6%
Other 3 9%
Unknown 13 41%
Readers by discipline Count As %
Business, Management and Accounting 5 16%
Computer Science 4 13%
Engineering 4 13%
Social Sciences 2 6%
Decision Sciences 1 3%
Other 3 9%
Unknown 13 41%