Mining Moving Object Data
Mining Moving Object Data
MoveMine is designed for sophisticated moving object data mining by integrating several functions. We explore the state-of-the-art and novel techniques at implementation of the selected functions. A user-friendly interface is provided to facilitate interactive exploration of mining results and flexible tuning of the underlying methods.
Please refer to this paper for the details of our functions:
Zhenhui Li, Bolin Ding, Fei Wu, Tobias Kin Hou Lei, Roland Kays, and Margaret Crofoot, Attraction and Avoidance Detection from Movements Proc. 2014 Int. Conf. on Very Large Data Bases (VLDB'14/PVLDB), Hangzhou, China, Sept. 2014.
Zhenhui Li, Fei Wu, and Margaret Crofoot, Mining Following Relationships in Movement Data, Proc. 2013 IEEE Int. Conf.on Data Mining (ICDM'13), Dallas, TX, Dec. 2013.
If you use this tool package to analyze your data, please cite the above paper using this bib file:
@ARTICLE{Li+13,
AUTHOR = {Zhenhui Li and Bolin Ding and Fei Wu and Tobias Kin Hou Lei and Roland Kays and Margaret Crofoot},
TITLE = {Attraction and Avoidance Detection from Movements},
JOURNAL = {Proceedings of the VLDB Endowment},
VOLUME = {5},
NUMBER = {3},
YEAR = {2013}
}
@INPROCEEDINGS{LWC13,
TITLE = {Mining Following Relationships in Movement Data},
AUTHOR = {Zhenhui Li and Fei Wu and Margaret Crofoot},
BOOKTITLE = {Proc. 2013 Int. Conf. Data Mining (ICDM'13)},
YEAR = {2013}
}
@INPROCEEDINGS{WLLH14,
TITLE = {MoveMine 2.0: Mining Object Relationships from Movement Data},
AUTHOR = {Fei Wu and Tobias Kin Hou Lei and Zhenhui Li and Jiawei Han},
BOOKTITLE = {Proc. 2014 Int. Conf. on Very Large Data Bases (VLDB'14/PVLDB},
ADDRESS = {Hangzhou, China},
MONTH = {Sep.},
YEAR = {2014}
}
MoveMine 1.0 was an earlier online version of the MoveMine system. We no longer maintain that MoveMine 1.0 system. You can watch the video of MoveMine 1.0 here .
Refer to the following paper for more details:
Zhenhui Li, Ming Ji, Jae-Gil Lee, LuAn Tang, Jiawei Han, Roland Kays, MoveMine: Mining Moving Object Databases, (system demo), Proc. 2010 ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'10), Indianapolis, Indiana, June 2010.
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