Monday, July 25, 2016

[DMANET] CFP in DMA for Business and Consumer Analytics

Subject: Call for papers to contribute to:

"Business and Consumer Analytics: New Directions" Volume 2
(Edited by Pablo Moscato & Natalie Jane de Vries, Publisher: Springer)

Dear distinguished researcher(s),

We are currently doing the first round of a call for papers for our contributed volume 2 of "Business and Consumer Analytics: New Directions". Volume 1 of this contributed book is well underway and will be published by Springer in 2017. We are seeking submission for Volume 2 with the first contributor draft deadline of March 31st 2017.

List of possible topic include (but are not limited to):

• Data mining methods for business analytics
o Text mining (incl. sentiment analysis)
o Pattern mining
o Mining graphs
o Feature selection methodologies
o Web mining
o Classification
o Clustering
o Online data stream mining
• Machine Learning (and/or Machine Teaching)
o Association rules
o Learning of semantics/sentiment/images
o Neural networks
o Consumer-related ethics and safety in machine learning
• Network analytics
o Complex network analytics
o Community detection
o Social network analysis
o Multiplex networks in business and marketing
• Predictive analytics
o Time-series prediction
o Churn prediction
o Recommender systems (E.g. cold-start problem, real-time/dynamic recommendations, etc.)
o Purchase prediction
• Evolutionary computation with business applications
o Business-related artificial intelligence
o Memetic algorithms for business applications
o Genetic programming
• Marketing Research
o Online consumer behavior analysis and prediction
o Market segmentation (clustering)
o Online advertising
o Social media research
o Social networking

• Logistics and Operations Research
o Topics in Urban Informatics
o Analytics for logistics and OR
o Decision support systems
o Analytics for 'greener' business practices

• New Optimization problems in Customer and Business Analytics
• Data and Information visualization
• Multi-objective optimization in business analytics
• Ranking with applications in business analytics

And any more related topics.

About the Volumes
These two volumes address the application of computer science, data mining, optimization and data-driven techniques to problems in the areas of business, marketing, consumer and social sciences. They aim to be an authoritative reference for these techniques in an area of science that is in essence a 'greenfield site'. An emphasis is on new personalised approaches.

Our aim is to present ideas that are thought-provoking and will motivate the readers to try more powerful analytic methods as well as introducing exciting new application domains to the 'hard-core' computer scientist.

The intended audience for these volumes includes highly advanced undergraduate students and mainly post-graduate level students and academic researchers. We also hope to generate interest from industry crowd with experience in computer and data science. Hence, contributions using 'real-life' datasets will be highly considered as these would be of great interest to an industry audience.

The list of topics is just a guideline that reflects the current development of the field. Not that any contribution using advanced analytics methods with a business/consumer focus will also be considered for acceptance in this volume.

Springer template guidelines will be followed for all contributions. We highly encourage contributors to prepare their work in Latex using the Author Springer template.

Please contact the Editors regarding any questions about the two volume series.

Pablo Moscato (Editor)
Natalie Jane de Vries (Editor)

School of Electrical Engineering and Computer Science
Faculty of Engineering and Built Environment
The University of Newcastle, Callaghan, NSW 2308, Australia
Phone: +61 (2) 49216056 (Prof. Moscato)

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