# liuhuanyong/TopicCluster

<https://repo.masters-masters.com/en/repos/liuhuanyong/TopicCluster>

[Home](https://repo.masters-masters.com/en) › [liuhuanyong](https://repo.masters-masters.com/en/owners/liuhuanyong) › [TopicCluster](https://repo.masters-masters.com/en/repos/liuhuanyong/TopicCluster)

liuhuanyong/TopicCluster has 246 stars on GitHub. Its RepoMasters card: Prototype tier. A simple documentary topic analysis implement based on traditional…

| Field | Value |
| --- | --- |
| Owner | [liuhuanyong](https://repo.masters-masters.com/en/owners/liuhuanyong) |
| Stars | 246 |
| Forks | 71 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2018 |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [liuhuanyong/TopicCluster](https://github.com/liuhuanyong/TopicCluster) |

## Repository

A simple documentary topic analysis implement based on traditional K-means and LDA which can achieve a not-bad result. 基于Kmeans与Lda模型的多文档主题聚类,输入多篇文档,输出每个主题的关键词与相应文本,可用于主题发现与热点分析等应用，如历时话题建模，评论画像等。

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.
