Thesis / Dissertation

Contrast Data Mining of Multi-source Heterogeneous Trajectory Data

Li Li, Sarah Monazam Erfani (ed.)

Published : 2020

Abstract

The rapid growth of location-acquisition and mobile computing techniques has led to an increasing availability of human trajectory data. This raises the challenge of detecting and understanding human mobility from these trajectory datasets to extract useful knowledge in a variety of domains, such as business management and urban computing. In this thesis, we focus on research into knowledge discovery from multi-source heterogeneous trajectory data. To be specific, five research questions in three scenarios are studied. The details are as follows. The first research question is how to perform trajectory pattern identification and anomaly detection for pedestrian flows. We propose to adopt co..

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