Go to main content
Formats
Format
BibTeX
MARCXML
TextMARC
MARC
DublinCore
EndNote
NLM
RefWorks
RIS

Linked e-resources

Details

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.

Browse Subjects

Show more subjects...

Statistics

from
to
Export