# A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques

arXiv: https://arxiv.org/abs/1707.02919 · HTML: https://mlsanity.com/paper/1707.02919/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jul 2017.

## Built on by (most cited first, 12 of 12)

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- [Enriching Social Science Research via Survey Item Linking](https://mlsanity.com/paper/2412.15831/) (2024)
- [Multivariate Gaussian Topic Modelling: A novel approach to discover topics with greater semantic coherence](https://mlsanity.com/paper/2503.15036/) (2025)

## Abstract (arXiv)

The amount of text that is generated every day is increasing dramatically. This tremendous volume of mostly unstructured text cannot be simply processed and perceived by computers. Therefore, efficient and effective techniques and algorithms are required to discover useful patterns. Text mining is the task of extracting meaningful information from text, which has gained significant attentions in recent years. In this paper, we describe several of the most fundamental text mining tasks and techniques including text pre-processing, classification and clustering. Additionally, we briefly explain text mining in biomedical and health care domains.