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Level: MSci, MSc
Title: Network-based analysis of purchasing patterns
Supervisor:

Dr Vincenzo Nicosia
Research Area: Complex Systems and Networks
Description:

Modelling online transaction data is the first step towards understanding user purchasing patterns, and bi-partite networks are a natural way to represent associations between products and consumers.

In this project the student will make use of recent advances in time series analysis, complex networks, and time varying graphs to construct network-based representations of online purchasing systems and to discover interesting properties of the data that can drive smart decisions in marketing products and pricing strategies.

 
Further Reading:

Literature suggestions will be supplied.
Key Modules:

MTH6139 Time Series

MTH6142 Complex Networks

MTH5121 Probability Models 

MTH6141 Random Processes 

 
Other Information:

The student should be confident with a programming language for scientific computing (possibly C/C++/Python/Matlab/Octave). The project could potentially become a springboard for an internship with one of our industrial partners.
Current Availability: Yes