Unsupervised Text Classification
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Benchmarks
Most implemented
Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches
Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics
Lex2Sent: A bagging approach to unsupervised sentiment analysis
DocSCAN: Unsupervised Text Classification via Learning from Neighbors
Papers
Dual Refinement Cycle Learning: Unsupervised Text Classification of Mamba and Community Detection on Text Attributed Graph
Pretrained language models offer strong text understanding capabilities but remain difficult to deploy in real-world text-attributed networks due to their heavy dependence on labeled data. Meanwhile, community detection …
Unsupervised Text ClassificationRepresentation LearningCommunity DetectionOne Size Does Not Fit All: Exploring Variable Thresholds for Distance-Based Multi-Label Text Classification
Distance-based unsupervised text classification is a method within text classification that leverages the semantic similarity between a label and a text to determine label relevance. This method provides numerous benefit…
Unsupervised Text ClassificationMulti-Label Text ClassificationMulti-Label ClassificationInformation RetrievalShuffle & Divide: Contrastive Learning for Long Text
We propose a self-supervised learning method for long text documents based on contrastive learning. A key to our method is Shuffle and Divide (SaD), a simple text augmentation algorithm that sets up a pretext task requir…
Contrastive LearningDocument EmbeddingSelf-Supervised LearningText Augmentation+3Text classification in shipping industry using unsupervised models and Transformer based supervised models
Obtaining labelled data in a particular context could be expensive and time consuming. Although different algorithms, including unsupervised learning, semi-supervised learning, self-learning have been adopted, the perfor…
ClassificationSelf-Learningtext-classificationText Classification+2Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches
Text classification of unseen classes is a challenging Natural Language Processing task and is mainly attempted using two different types of approaches. Similarity-based approaches attempt to classify instances based on …
Classificationtext-classificationText ClassificationUnsupervised Text Classification+1Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics
In this paper, we consider the task of retrieving documents with predefined topics from an unlabeled document dataset using an unsupervised approach. The proposed unsupervised approach requires only a small number of key…
Document ClassificationRetrievalUnsupervised Text ClassificationWorld Knowledge