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Business and Consumer Analytics: New Ideas

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Cover of 'Business and Consumer Analytics: New Ideas'

Table of Contents

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    Book Overview
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    Chapter 1 Marketing Meets Data Science: Bridging the Gap
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    Chapter 2 Consumer Behaviour and Marketing Fundamentals for Business Data Analytics
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    Chapter 4 An Introduction to Proximity Graphs
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    Chapter 5 Clustering Consumers and Cluster-Specific Behavioural Models
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    Chapter 6 Frequent Itemset Mining
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    Chapter 8 Centrality in Networks: Finding the Most Important Nodes
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    Chapter 9 Overlapping Communities in Co-purchasing and Social Interaction Graphs: A Memetic Approach
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    Chapter 10 Taming a Graph Hairball: Local Exploration in a Global Context
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    Chapter 11 Network-Based Models for Social Recommender Systems
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    Chapter 12 Using Network Alignment to Identify Conserved Consumer Behaviour Modelling Constructs
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    Chapter 13 Memetic Algorithms for Business Analytics and Data Science: A Brief Survey
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    Chapter 14 A Memetic Algorithm for the Team Orienteering Problem
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    Chapter 15 A Memetic Algorithm for Competitive Facility Location Problems
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    Chapter 16 Visualizing Products and Consumers: A Gestalt Theory Inspired Method
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    Chapter 17 An Overview of Meta-Analytics: The Promise of Unifying Metaheuristics and Analytics
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    Chapter 18 From Ensemble Learning to Meta-Analytics: A Review on Trends in Business Applications
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    Chapter 19 Metaheuristics and Classifier Ensembles
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    Chapter 20 A Multi-objective Meta-Analytic Method for Customer Churn Prediction
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    Chapter 21 Hotel Classification Using Meta-Analytics: A Case Study with Cohesive Clustering
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    Chapter 23 Towards Personalized Data-Driven Bundle Design with QoS Constraint
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    Chapter 25 New Ideas in Ranking for Personalized Fashion Recommender Systems
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    Chapter 26 Datasets for Business and Consumer Analytics
Attention for Chapter 13: Memetic Algorithms for Business Analytics and Data Science: A Brief Survey
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Chapter title
Memetic Algorithms for Business Analytics and Data Science: A Brief Survey
Chapter number 13
Book title
Business and Consumer Analytics: New Ideas
Published by
Springer, Cham, May 2019
DOI 10.1007/978-3-030-06222-4_13
Book ISBNs
978-3-03-006221-7, 978-3-03-006222-4

Pablo Moscato, Luke Mathieson, Moscato, Pablo, Mathieson, Luke

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 12%
Lecturer 2 5%
Student > Master 2 5%
Student > Bachelor 1 2%
Professor 1 2%
Other 3 7%
Unknown 28 67%
Readers by discipline Count As %
Engineering 5 12%
Computer Science 4 10%
Business, Management and Accounting 2 5%
Biochemistry, Genetics and Molecular Biology 1 2%
Unknown 30 71%