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dynamic-topic-modeling-1.1.0
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مشاهده بیشترتوضیحات
Run dynamic topic modeling
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | dynamic-topic-modeling-1.1.0 |
| نام | dynamic-topic-modeling |
| نسخه کتابخانه | 1.1.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Jiaxiang Li and Shuyi Wang and Svitlana Galeshchuk |
| ایمیل نویسنده | alex.lijiaxiang@foxmail.com |
| آدرس صفحه اصلی | https://github.com/JiaxiangBU/dynamic_topic_modeling |
| آدرس اینترنتی | https://pypi.org/project/dynamic-topic-modeling/ |
| مجوز | Apache Software License 2.0 |
# dynamic_topic_modeling
> Run dynamic topic modeling.
<!-- README.md is generated from README.Rmd. Please edit that file -->
<!-- badges: start -->
[](https://badge.fury.io/py/dynamic-topic-modeling)
[](https://zenodo.org/badge/latestdoi/238671296)
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The goal of 'wei_lda_debate' is to build Latent Dirichlet Allocation
models based on 'sklearn' and 'gensim' framework, and Dynamic Topic
Model(Blei and Lafferty 2006) based on 'gensim' framework. I decide to
build a Python package 'dynamic_topic_modeling', so this reposority
will be updated and 'wei_lda_debate' is depreciated. The new
reposority path is
<https://github.com/JiaxiangBU/dynamic_topic_modeling.git>.
To build this package, I borrow from
1. 'wei_lda_debate'(Wang 2018) to build LDA framework
2. 'dtmvisual'(Svitlana 2019) to build the visualization framework.
Moreover, this package seems like a visualiztaion tutorial using
jupyter notebook for 'dtmvisual'.
1. [LDA based on
sklearn](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/sklearn-lda.ipynb)
2. [LDA based on
gensim](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/gensim-lda.ipynb)
3. [Dynamic Topic
Modeling](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/dtm.ipynb)
4. [Data Analysis on Demi Gods and Semi Devils using Dynamic Topic
Modeling](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/demo.ipynb)
Jiaxiang Li. (2020, February 9). JiaxiangBU/dynamic_topic_modeling:
dynamic_topic_modeling 1.1.0 (Version v1.1.0). Zenodo.
<http://doi.org/10.5281/zenodo.3660401>
```
@software{jiaxiang_li_2020_3660401,
author = {Jiaxiang Li},
title = {{JiaxiangBU/dynamic_topic_modeling:
dynamic_topic_modeling 1.1.0}},
month = feb,
year = 2020,
publisher = {Zenodo},
version = {v1.1.0},
doi = {10.5281/zenodo.3660401},
url = {https://doi.org/10.5281/zenodo.3660401}
}
```
If you use dynamic_topic_modeling, I would be very grateful if you can
add a citation in your published work. By citing
dynamic_topic_modeling, beyond acknowledging the work, you contribute
to make it more visible and guarantee its growing and sustainability.
For citation, please use the BibTex or the citation content.
## Install
`pip install dynamic_topic_modeling`
## How to use
1. [LDA based on
sklearn](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/sklearn-lda.ipynb)
2. [LDA based on
gensim](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/gensim-lda.ipynb)
3. [Dynamic Topic
Modeling](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/dtm.ipynb)
4. [Data Analysis on Demi Gods and Semi Devils using Dynamic Topic
Modeling](https://nbviewer.jupyter.org/urls/jiaxiangbu.github.io/dynamic_topic_modeling/demo.ipynb)
Jiaxiang Li. (2020, February 9). JiaxiangBU/dynamic\_topic\_modeling:
dynamic\_topic\_modeling 1.1.0 (Version v1.1.0). Zenodo.
<http://doi.org/10.5281/zenodo.3660401>
```
@software{jiaxiang_li_2020_3660401,
author = {Jiaxiang Li},
title = {{JiaxiangBU/dynamic\_topic\_modeling:
dynamic\_topic\_modeling 1.1.0}},
month = feb,
year = 2020,
publisher = {Zenodo},
version = {v1.1.0},
doi = {10.5281/zenodo.3660401},
url = {https://doi.org/10.5281/zenodo.3660401}
}
```
If you use dynamic\_topic\_modeling, I would be very grateful if you can
add a citation in your published work. By citing
dynamic\_topic\_modeling, beyond acknowledging the work, you contribute
to make it more visible and guarantee its growing and sustainability.
For citation, please use the BibTex or the citation content.
<h4 align="center">
**Code of Conduct**
</h4>
<h6 align="center">
Please note that the `dynamic_topic_modeling` project is released with a
[Contributor Code of
Conduct](https://github.com/JiaxiangBU/dynamic_topic_modeling/blob/master/CODE_OF_CONDUCT.md).<br>By
contributing to this project, you agree to abide by its terms.
</h6>
<h4 align="center">
**License**
</h4>
<h6 align="center">
Apache License c [Jiaxiang Li;Shuyi Wang;Svitlana
Galeshchuk](https://github.com/JiaxiangBU/dynamic_topic_modeling/blob/master/LICENSE.md)
</h6>
<div id="refs" class="references">
<div id="ref-Blei2006Dynamic">
Blei, David M., and John D. Lafferty. 2006. "Dynamic Topic Models." In
*Machine Learning, Proceedings of the Twenty-Third International
Conference (Icml 2006), Pittsburgh, Pennsylvania, Usa, June 25-29,
2006*.
</div>
<div id="ref-Svitlana_2019">
Svitlana. 2019. "Dtmvisual: This Package Consists of Functionalities for
Dynamic Topic Modelling and Its Visualization." GitHub. 2019.
<https://github.com/GSukr/dtmvisual>.
</div>
<div id="ref-Shuyi_Wang2018">
Wang, Shuyi. 2018. GitHub. 2018.
<https://github.com/wshuyi/wei_lda_debate>.
</div>
</div>
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl dynamic-topic-modeling-1.1.0:
pip install dynamic-topic-modeling-1.1.0.whl
نصب پکیج tar.gz dynamic-topic-modeling-1.1.0:
pip install dynamic-topic-modeling-1.1.0.tar.gz