goamegah/Short-Text-Clustering

Short text clustering methods through differents approaches

20
/ 100
Experimental

This tool helps you organize collections of short texts, like social media posts, search queries, or product reviews, into meaningful groups. You provide a list of short text snippets, and it sorts them into clusters based on their similarity, making it easier to identify common themes or topics. Anyone who needs to make sense of large volumes of brief textual data, such as market researchers, customer feedback analysts, or content strategists, would find this useful.

No commits in the last 6 months.

Use this if you need to quickly categorize many short text entries and understand the underlying topics without manually reading through each one.

Not ideal if your data consists of very long documents, as this is specifically optimized for brevity, or if you need to classify texts into predefined categories.

text-analysis topic-discovery customer-feedback social-listening content-categorization
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 0 / 25

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Stars

7

Forks

Language

Python

License

Apache-2.0

Last pushed

May 27, 2024

Commits (30d)

0

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