# MAT-clustering: Summarization Methods for Multiple Aspect Trajectory Data Mining \[MAT-Tools Framework\]
---
\[[Publication](#)\] \[[citation.bib](citation.bib)\] \[[GitHub](https://github.com/mat-analysis/mat-matclustering)\] \[[PyPi](https://pypi.org/project/mat-matclustering/)\]
The present application offers a tool, to support the user in the data mining task of multiple aspect trajectories, specifically for clustering its complex data. It integrates into a unique platform the fragmented approaches available for multiple aspects trajectories and in general for multidimensional sequence classification into a unique web-based and python library system.
Created on Apr, 2024
Copyright (C) 2024, License GPL Version 3 or superior (see LICENSE file)
### Main Modules
### Installation
Install directly from PyPi repository, or, download from github. (python >= 3.7 required)
```bash
pip install matclustering
```
### Citing
If you use `matclustering` please cite the following paper:
Tarlis Tortelli Portela; Jonata Tyska Carvalho; Vania Bogorny. HiPerMovelets: high-performance movelet extraction for trajectory classification, International Journal of Geographical Information Science, 2022. DOI: 10.1080/13658816.2021.2018593.
[Bibtex](citation.bib):
```bash
@article{Portela2022,
author = {Tarlis Tortelli Portela and Jonata Tyska Carvalho and Vania Bogorny},
title = {HiPerMovelets: high-performance movelet extraction for trajectory classification},
journal = {International Journal of Geographical Information Science},
volume = {0},
number = {0},
pages = {1-25},
year = {2022},
publisher = {Taylor & Francis},
doi = {10.1080/13658816.2021.2018593},
URL = {https://doi.org/10.1080/13658816.2021.2018593}
}
```
### Collaborate with us
Any contribution is welcome. This is an active project and if you would like to include your algorithm in `matclustering`, feel free to fork the project, open an issue and contact us.
Feel free to contribute in any form, such as scientific publications referencing `matclustering`, teaching material and workshop videos.
### Related packages
This package is part of _MAT-Tools Framework_ for Multiple Aspect Trajectory Data Mining, check the guide project:
- **[mat-tools](https://github.com/mat-analysis/mat-tools)**: Reference guide for MAT-Tools Framework repositories
And others:
### Change Log
This is a package under construction, see [CHANGELOG.md](./CHANGELOG.md)
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"description": "# MAT-clustering: Summarization Methods for Multiple Aspect Trajectory Data Mining \\[MAT-Tools Framework\\]\n---\n\n\\[[Publication](#)\\] \\[[citation.bib](citation.bib)\\] \\[[GitHub](https://github.com/mat-analysis/mat-matclustering)\\] \\[[PyPi](https://pypi.org/project/mat-matclustering/)\\]\n\n\nThe present application offers a tool, to support the user in the data mining task of multiple aspect trajectories, specifically for clustering its complex data. It integrates into a unique platform the fragmented approaches available for multiple aspects trajectories and in general for multidimensional sequence classification into a unique web-based and python library system. \n\nCreated on Apr, 2024\nCopyright (C) 2024, License GPL Version 3 or superior (see LICENSE file)\n\n### Main Modules\n\n\n\n### Installation\n\nInstall directly from PyPi repository, or, download from github. (python >= 3.7 required)\n\n```bash\n pip install matclustering\n```\n\n### Citing\n\nIf you use `matclustering` please cite the following paper:\n\n Tarlis Tortelli Portela; Jonata Tyska Carvalho; Vania Bogorny. HiPerMovelets: high-performance movelet extraction for trajectory classification, International Journal of Geographical Information Science, 2022. DOI: 10.1080/13658816.2021.2018593.\n\n[Bibtex](citation.bib):\n\n```bash\n@article{Portela2022,\n author = {Tarlis Tortelli Portela and Jonata Tyska Carvalho and Vania Bogorny},\n title = {HiPerMovelets: high-performance movelet extraction for trajectory classification},\n journal = {International Journal of Geographical Information Science},\n volume = {0},\n number = {0},\n pages = {1-25},\n year = {2022},\n publisher = {Taylor & Francis},\n doi = {10.1080/13658816.2021.2018593},\n URL = {https://doi.org/10.1080/13658816.2021.2018593}\n}\n```\n\n### Collaborate with us\n\nAny contribution is welcome. This is an active project and if you would like to include your algorithm in `matclustering`, feel free to fork the project, open an issue and contact us.\n\nFeel free to contribute in any form, such as scientific publications referencing `matclustering`, teaching material and workshop videos.\n\n### Related packages\n\nThis package is part of _MAT-Tools Framework_ for Multiple Aspect Trajectory Data Mining, check the guide project:\n\n- **[mat-tools](https://github.com/mat-analysis/mat-tools)**: Reference guide for MAT-Tools Framework repositories\n\nAnd others:\n\n\n\n### Change Log\n\nThis is a package under construction, see [CHANGELOG.md](./CHANGELOG.md)\n",
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