Towards the Discovery of Genuine Social Groups from Mobility Data

Htoo Htet Aung, Nay Aung Lwin, Phyo Phyo

semanticscholar(2018)

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摘要
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. KeywordsReal-time Data Mining, Mobility Data
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