Mining individual significant places from historical trajectory data-Reference-Cited by-同舟云学术

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Mining individual significant places from historical trajectory data

Published:2023 Issue: Volume: Page:15-26
ISSN:
Container-title:Handbook of Mobility Data Mining
language:
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Author:

Li Wenjing^ORCID,Zhang Haoran,Shibasaki Ryosuke,Chen Jinyu,Kobayashi Hill Hiroki

Publisher

Elsevier

Reference24 articles.

1. Mining individual similarity by assessing interactions with personally significant places from GPS trajectories;Yang;ISPRS International Journal of Geo-Information.,2018

2. Mining personally important places from GPS tracks;Zhou,2007

3. Using GPS to learn significant locations and predict movement across multiple users;Ashbrook;Personal and Ubiquitous Computing,2003

4. Metagraph-based life pattern clustering with big human mobility data;Li;IEEE Transactions on Big Data,2022

5. ST‐DMQL: a semantic trajectory data mining query language;Bogorny;International Journal of Geographical Information Science,2009

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