Authors:
Rui Sarmento
1
;
Mário Cordeiro
2
and
João Gama
1
Affiliations:
1
University of Porto, Portugal
;
2
LIAAD/INESC TEC, Portugal
Keyword(s):
Large Scale Social Networks Sampling, Data Streams, Telecommunication Networks, top-K Networks.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Data Engineering
;
Data Mining
;
Databases and Data Security
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Industrial Applications of Artificial Intelligence
;
Large Scale Databases
;
Query Languages and Query Processing
;
Sensor Networks
;
Signal Processing
;
Soft Computing
Abstract:
The combination of top-K network representation of the data stream with community detection is a novel
approach to streaming networks sampling. Keeping an always up-to-date sample of the full network, the
advantage of this method, compared to previous, is that it preserves larger communities and original network
distribution. Empirically, it will also be shown that these techniques, in conjunction with community detection,
provide effective ways to perform sampling and analysis of large scale streaming networks with power law
distributions.