Imperial College London
Alternate

ProfessorPeterHarrison

Faculty of Engineering, Department of Computing

Emeritus Professor in Mathematical Modelling
 
 
 
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Contact

 

+44 (0)20 7594 8363p.harrison Website

 
 
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Location

 

353Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Chis:2014:10.1109/MASCOTS.2014.29,
author = {Chis, T and Harrison, PG},
doi = {10.1109/MASCOTS.2014.29},
pages = {168--173},
publisher = {IEEE},
title = {Modeling multi-user behaviour in social networks},
url = {http://dx.doi.org/10.1109/MASCOTS.2014.29},
year = {2014}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - Social networks, and the behaviour of groups of online users, are popular topics in modeling and classifying Internet traffic data. There is a need to analyze online network performance metrics through suitable workload benchmarks. We address this issue with a Multi-dimensional Hidden Markov Model (MultiHMM) to act as a Multi-User workload classifier. The MultiHMM is an adaptation of the original HMM, using clustering methods and multiple trace-training for the Baum-Welch algorithm. The goals of the MultiHMM are to classify multiple online user streams with minimal processing needs, represent burstiness and correlation among groups of users and to improve security measures in the social network. Experiments are carried out using multiple traces from Twitter data, where original traces are analysed and compared with the MultiHMM-generated traces. The metrics involved in validating our model include means, standard deviations, skew ness and autocorrelation, and we discuss applications and extensions of our model.
AU  - Chis,T
AU  - Harrison,PG
DO  - 10.1109/MASCOTS.2014.29
EP  - 173
PB  - IEEE
PY  - 2014///
SN  - 1526-7539
SP  - 168
TI  - Modeling multi-user behaviour in social networks
UR  - http://dx.doi.org/10.1109/MASCOTS.2014.29
UR  - http://hdl.handle.net/10044/1/26126
ER  -
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