Papers › Self-Taught Convolutional Neural Networks for Short Text Clustering

Self-Taught Convolutional Neural Networks for Short Text Clustering

1 Jan 2017arXiv:1701.00185archive 2025-07-28

Jiaming Xu, Peng Wang, Suncong Zheng, Guanhua Tian, Jun Zhao, Bo Xu

Short text clustering is a challenging problem due to its sparseness of text representation. Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text Clustering (dubbed STC^2), which can flexibly and successfully incorporate more useful semantic features and learn non-biased deep text representation in an unsupervised manner. In our framework, the original raw text features are firstly embedded into compact binary codes by using one existing unsupervised dimensionality reduction methods. Then, word embeddings are explored and fed into convolutional neural networks to learn deep feature representations, meanwhile the output units are used to fit the pre-trained binary codes in the training process. Finally, we get the optimal clusters by employing K-means to cluster the learned representations. Extensive experimental results demonstrate that the proposed framework is effective, flexible and outperform several popular clustering methods when tested on three public short text datasets.

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jacoxu/STC2 officialmentioned in papermentioned on GitHubtf report

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Tasks

Clustering Dimensionality Reduction Short Text Clustering Text Clustering Word Embeddings

Results from the paper archive 2025-07-28

Task	Dataset	Model	Metric	Value	Rank at snapshot	Leaderboard	Report
Short Text Clustering	Biomedical	STC2-LE	Acc	43.62	#3 of 4	Archive leaderboard	report
Short Text Clustering	Biomedical	STC2-LPI	Acc	43	#4 of 4	Archive leaderboard	report
Short Text Clustering	Searchsnippets	STC2-LE	Acc	77.09	#3 of 4	Archive leaderboard	report
Short Text Clustering	Searchsnippets	STC2-LPI	Acc	77.01	#4 of 4	Archive leaderboard	report
Short Text Clustering	Stackoverflow	Deep ECIC	Acc	STC2-LE	#4 of 5	Archive leaderboard	report
Short Text Clustering	Stackoverflow	Deep ECIC	Acc	STC2-LPI	#5 of 5	Archive leaderboard	report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

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