mat-similarity


Namemat-similarity JSON
Version 0.1rc1 PyPI version JSON
download
home_pagehttps://github.com/mat-analysis/mat-similarity
SummarySimilarity Methods and Functions for Multiple Aspect Trajectory Data Mining
upload_time2024-10-02 03:33:58
maintainerNone
docs_urlNone
authorVanessa Lago Machado
requires_python<3.10
licenseGPL Version 3 or superior (see LICENSE file)
keywords data-science machine-learning data-mining trajectory multiple-trajectory similarity
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # MAT-similarity: Similarity Methods and Functions for Multiple Aspect Trajectory Data Mining \[MAT-Tools Framework\]
---

\[[Publication](#)\] \[[Bibtex](https://github.com/mat-analysis/mat-tools/blob/main/references/mat-tools.bib)\] \[[GitHub](https://github.com/mat-analysis/mat-similarity)\] \[[PyPi](https://pypi.org/project/mat-similarity/)\]


The present application offers a tool, to support the user in the data mining task of multiple aspect trajectories, specifically for **measuring similarity** of 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

The implemented similarity measure classes for MAT:

1. **MUITAS**: Semantic-Aware Multiple-Aspect Trajectory Similarity measure.
2. **MSM**: Multidimensional similarity measuring for semantic trajectories.
3. **LCSS**: Longest Common Subsequence MAT similarity measure.
4. **EDR**: Edit Distance on Real sequences MAT similarity measure.

### Installation

Install directly from PyPi repository, or, download from github. (python >= 3.7 required)

```bash
    pip install mat-similarity
```

### Citing

If you use `mat-similarity` please cite the following paper:

 - Portela, T. T.; Machado, V. L.; Renso, C. Unified Approach to Trajectory Data Mining and Multi-Aspect Trajectory Analysis with MAT-Tools Framework. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 39. , 2024, Florianópolis/SC. \[[Bibtex](https://github.com/mat-analysis/mat-tools/blob/main/references/mat-tools.bib)\]

### Collaborate with us

Any contribution is welcome. This is an active project and if you would like to include your code, feel free to fork the project, open an issue and contact us.

Feel free to contribute in any form, such as scientific publications referencing this package, 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

### Change Log

This is a package under construction, see [CHANGELOG.md](https://github.com/mat-analysis/mat-similarity/blob/main/CHANGELOG.md)

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/mat-analysis/mat-similarity",
    "name": "mat-similarity",
    "maintainer": null,
    "docs_url": null,
    "requires_python": "<3.10",
    "maintainer_email": "Tarlis Tortelli Portela <tarlis@tarlis.com.br>, Vanessa Lago Machado <vanessalagomachado@gmail.com>",
    "keywords": "data-science, machine-learning, data-mining, trajectory, multiple-trajectory, similarity",
    "author": "Vanessa Lago Machado",
    "author_email": "Vanessa Lago Machado <vanessalagomachado@gmail.com>, Tarlis Tortelli Portela <tarlis@tarlis.com.br>",
    "download_url": "https://files.pythonhosted.org/packages/18/59/e933baeb00ce5727fa0ebbcaa493468660d16350eeb0794a773d6e965f90/mat_similarity-0.1rc1.tar.gz",
    "platform": null,
    "description": "# MAT-similarity: Similarity Methods and Functions for Multiple Aspect Trajectory Data Mining \\[MAT-Tools Framework\\]\n---\n\n\\[[Publication](#)\\] \\[[Bibtex](https://github.com/mat-analysis/mat-tools/blob/main/references/mat-tools.bib)\\] \\[[GitHub](https://github.com/mat-analysis/mat-similarity)\\] \\[[PyPi](https://pypi.org/project/mat-similarity/)\\]\n\n\nThe present application offers a tool, to support the user in the data mining task of multiple aspect trajectories, specifically for **measuring similarity** of 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\nThe implemented similarity measure classes for MAT:\n\n1. **MUITAS**: Semantic-Aware Multiple-Aspect Trajectory Similarity measure.\n2. **MSM**: Multidimensional similarity measuring for semantic trajectories.\n3. **LCSS**: Longest Common Subsequence MAT similarity measure.\n4. **EDR**: Edit Distance on Real sequences MAT similarity measure.\n\n### Installation\n\nInstall directly from PyPi repository, or, download from github. (python >= 3.7 required)\n\n```bash\n    pip install mat-similarity\n```\n\n### Citing\n\nIf you use `mat-similarity` please cite the following paper:\n\n - Portela, T. T.; Machado, V. L.; Renso, C. Unified Approach to Trajectory Data Mining and Multi-Aspect Trajectory Analysis with MAT-Tools Framework. In: SIMP\u00d3SIO BRASILEIRO DE BANCO DE DADOS (SBBD), 39. , 2024, Florian\u00f3polis/SC. \\[[Bibtex](https://github.com/mat-analysis/mat-tools/blob/main/references/mat-tools.bib)\\]\n\n### Collaborate with us\n\nAny contribution is welcome. This is an active project and if you would like to include your code, 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 this package, 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\n### Change Log\n\nThis is a package under construction, see [CHANGELOG.md](https://github.com/mat-analysis/mat-similarity/blob/main/CHANGELOG.md)\n",
    "bugtrack_url": null,
    "license": "GPL Version 3 or superior (see LICENSE file)",
    "summary": "Similarity Methods and Functions for Multiple Aspect Trajectory Data Mining",
    "version": "0.1rc1",
    "project_urls": {
        "Bug Tracker": "https://github.com/mat-analysis/mat-similarity/issues",
        "Documentation": "https://mat-analysis.github.io/mat-tools/mat-similarity/index.html",
        "Download": "https://pypi.org/project/mat-similarity/#files",
        "Homepage": "https://github.com/mat-analysis/mat-similarity",
        "Repository": "https://github.com/mat-analysis/mat-similarity"
    },
    "split_keywords": [
        "data-science",
        " machine-learning",
        " data-mining",
        " trajectory",
        " multiple-trajectory",
        " similarity"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "990c6de0b3a00b213561a7c36f079e53b26539102b73fc31e19818c81dd0eddd",
                "md5": "7afb77a470fe2cda0760bff845547706",
                "sha256": "a15ad2e0de23b867622da097b927f71c2703a0cf9a2e3f4f786c90f77426437c"
            },
            "downloads": -1,
            "filename": "mat_similarity-0.1rc1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "7afb77a470fe2cda0760bff845547706",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": "<3.10",
            "size": 40172,
            "upload_time": "2024-10-02T03:33:55",
            "upload_time_iso_8601": "2024-10-02T03:33:55.698099Z",
            "url": "https://files.pythonhosted.org/packages/99/0c/6de0b3a00b213561a7c36f079e53b26539102b73fc31e19818c81dd0eddd/mat_similarity-0.1rc1-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "1859e933baeb00ce5727fa0ebbcaa493468660d16350eeb0794a773d6e965f90",
                "md5": "836b303e1a3f2e191b3d2d0ffc0de013",
                "sha256": "0ae3d9cfef3a37be7feee0295429ef7d1cd2c4c9e609182eac1241bcf556349a"
            },
            "downloads": -1,
            "filename": "mat_similarity-0.1rc1.tar.gz",
            "has_sig": false,
            "md5_digest": "836b303e1a3f2e191b3d2d0ffc0de013",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": "<3.10",
            "size": 2961278,
            "upload_time": "2024-10-02T03:33:58",
            "upload_time_iso_8601": "2024-10-02T03:33:58.907639Z",
            "url": "https://files.pythonhosted.org/packages/18/59/e933baeb00ce5727fa0ebbcaa493468660d16350eeb0794a773d6e965f90/mat_similarity-0.1rc1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-10-02 03:33:58",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "mat-analysis",
    "github_project": "mat-similarity",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "mat-similarity"
}
        
Elapsed time: 0.38587s