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Table of Contents
1 Marketing meets Data Science: Bridging the gap
2 Consumer behaviour and marketing fundamentals for business data analytics
3 Introducing Clustering with a focus in Marketing and Consumer Analytics
4 An Introduction to Proximity Graphs
5 Clustering consumers and cluster-specific behavioural models
6 Frequent Itemset Mining
7 Business Network Analytics: From Graphs to Supernetworks
8 Centrality in networks: Finding the most important nodes
9 Overlapping communities in co-purchasing and social interaction graphs: a memetic approach
10 Taming a Graph Hairball: Local Exploration in a Global Context
11 Network-based models for social recommender systems
12 Using Network Alignment to Identify Consumer Behaviour Modeling Constructs
13 Memetic Algorithms for Business Analytics and Data Science: A Brief Survey
14 A Memetic Algorithm for the Team Orienteering Problem
15 A Memetic Algorithm for Competitive Facility Location Problems
15 Visualizing Products and Consumers: A Gestalt Theory inspired method
16 Visualizing Products and Consumers: A Gestalt Theory inspired method
17 An overview of Meta-Analytics: The Promise of Unifying Metaheuristics and Analytics
18 From Ensemble Learning to Meta-Analytics: A Review on Trends in Business Applications
19 Metaheuristics and Classifier Ensembles
20 A Multi-objective Meta-Analytic Method for Customer Churn Prediction
21 Hotel classification using meta-analytics: a case study with cohesive clustering
22 Fuzzy clustering in travel and tourism analytics
23 Towards Personalized Data-Driven Bundle Design with QoS Constraint
24 A fuzzy evaluation of tourism sustainability
25 New Ideas in ranking for Personalised Fashion Recommender Systems
26 Datasets for Business and Consumer Analytics.
2 Consumer behaviour and marketing fundamentals for business data analytics
3 Introducing Clustering with a focus in Marketing and Consumer Analytics
4 An Introduction to Proximity Graphs
5 Clustering consumers and cluster-specific behavioural models
6 Frequent Itemset Mining
7 Business Network Analytics: From Graphs to Supernetworks
8 Centrality in networks: Finding the most important nodes
9 Overlapping communities in co-purchasing and social interaction graphs: a memetic approach
10 Taming a Graph Hairball: Local Exploration in a Global Context
11 Network-based models for social recommender systems
12 Using Network Alignment to Identify Consumer Behaviour Modeling Constructs
13 Memetic Algorithms for Business Analytics and Data Science: A Brief Survey
14 A Memetic Algorithm for the Team Orienteering Problem
15 A Memetic Algorithm for Competitive Facility Location Problems
15 Visualizing Products and Consumers: A Gestalt Theory inspired method
16 Visualizing Products and Consumers: A Gestalt Theory inspired method
17 An overview of Meta-Analytics: The Promise of Unifying Metaheuristics and Analytics
18 From Ensemble Learning to Meta-Analytics: A Review on Trends in Business Applications
19 Metaheuristics and Classifier Ensembles
20 A Multi-objective Meta-Analytic Method for Customer Churn Prediction
21 Hotel classification using meta-analytics: a case study with cohesive clustering
22 Fuzzy clustering in travel and tourism analytics
23 Towards Personalized Data-Driven Bundle Design with QoS Constraint
24 A fuzzy evaluation of tourism sustainability
25 New Ideas in ranking for Personalised Fashion Recommender Systems
26 Datasets for Business and Consumer Analytics.