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  1. University of Information Technology
  2. International Conference on Advanced Information Technologies

Towards the Discovery of Genuine Social Groups from Mobility Data

http://hdl.handle.net/20.500.12678/0000006295
http://hdl.handle.net/20.500.12678/0000006295
9f046e70-a236-4988-a0ce-fc68dd3985b7
0097e471-9c9e-410e-bd9a-1187976b5ee1
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Towards Towards the Discovery of Genuine Social Groups from Mobility Data.pdf (1.7 Mb)
© 2018 ICAIT
Publication type
Conference paper
Upload type
Publication
Title
Title Towards the Discovery of Genuine Social Groups from Mobility Data
Language en
Publication date 2018-11-02
Authors
Htoo Htet Aung
Nay Aung Lwin
Phyo Phyo San
Description
Extraction of social groups from human mobility datasets
has been regarded as convoy mining problem since a
convoy (defined as a group of people which are spatially
close to each other across time) is customarily assumed to
represent a social group. However, social groups cannot
be modelled trivially as a convoy as empirical evidence
suggests convoy mining will report many ‘false positives’
and miss some ‘false negatives’. We propose a two-step
method to discover social groups from human mobility
data in real-time. To the best of our knowledge, this paper
is the first attempt to discover genuine social groups from
mobility data. Experiments on the real-life dataset
indicate that our two-step approach can accurately and
efficiently discover genuine social groups.
Keywords
Real-time Data Mining, Mobility Data
Conference papers
ICAIT-2018
1-2 November, 2018
2nd International Conference on Advanced Information Technologies
Yangon, Myanmar
Data Mining
https://www.uit.edu.mm/icait-2018/
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