TY - JOUR
T1 - MoveMine 2.0
T2 - Mining object relationships from movement data
AU - Wu, Fei
AU - Lei, Tobias Kin Hou
AU - Li, Zhenhui
AU - Han, Jiawei
PY - 2014
Y1 - 2014
N2 - The development in positioning technology has enabled us to collect a huge amount of movement data from moving objects, such as human, animals, and vehicles. The data embed rich information about the relationships among moving objects and have applications in many fields, e.g., in ecological study and human behavioral study. Previously, we have proposed a system MoveMine that integrates several start-of-art movement mining methods. However, it does not include recent methods on relationship pattern mining. Thus, we propose to extend MoveMine to MoveMine 2.0 by adding substantial new methods in mining dynamic relationship patterns. Newly added methods focus on two types of pairwise relationship patterns: (i) attraction/avoidance relationship, and (ii) following pattern. A user-friendly interface is designed to support interactive exploration of the result and provides exibility in tuning parameters. MoveMine 2.0 is tested on multiple types of real datasets to ensure its practical use. Our system provides useful tools for domain experts to gain insights on real dataset. Meanwhile, it will promote further research in relationship mining from moving objects.
AB - The development in positioning technology has enabled us to collect a huge amount of movement data from moving objects, such as human, animals, and vehicles. The data embed rich information about the relationships among moving objects and have applications in many fields, e.g., in ecological study and human behavioral study. Previously, we have proposed a system MoveMine that integrates several start-of-art movement mining methods. However, it does not include recent methods on relationship pattern mining. Thus, we propose to extend MoveMine to MoveMine 2.0 by adding substantial new methods in mining dynamic relationship patterns. Newly added methods focus on two types of pairwise relationship patterns: (i) attraction/avoidance relationship, and (ii) following pattern. A user-friendly interface is designed to support interactive exploration of the result and provides exibility in tuning parameters. MoveMine 2.0 is tested on multiple types of real datasets to ensure its practical use. Our system provides useful tools for domain experts to gain insights on real dataset. Meanwhile, it will promote further research in relationship mining from moving objects.
UR - http://www.scopus.com/inward/record.url?scp=84905814581&partnerID=8YFLogxK
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U2 - 10.14778/2733004.2733043
DO - 10.14778/2733004.2733043
M3 - Article
AN - SCOPUS:84905814581
VL - 7
SP - 1613
EP - 1616
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
SN - 2150-8097
IS - 13
ER -