Text Clustering
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Benchmarks
Most implemented
MTEB: Massive Text Embedding Benchmark
Short Text Clustering via Convolutional Neural Networks
Proposition-Level Clustering for Multi-Document Summarization
Supporting Clustering with Contrastive Learning
Discovering New Intents with Deep Aligned Clustering
Dissimilarity Mixture Autoencoder for Deep Clustering
Papers
CLUBench: A Clustering Benchmark
Clustering is a fundamental problem in data science with a long-standing research history, yielding numerous insightful algorithms. Despite this progress, a systematic and large-scale empirical evaluation that jointly co…
Text ClusteringDeep ClusteringTextClusterLab: An Integrated Framework for Reliable Text Clustering Studies
In recent years, text clustering has become a critical technique for applications including intent discovery, topic mining, and recommendation systems. However, evaluating text clustering algorithms remains challenging s…
Recommendation SystemsIntent DiscoveryText ClusteringAdaGraph: A Graph-Native Clustering Algorithm That Overcomes the Curse of Dimensionality and Enables Scientific Discovery
We present AdaGraph, a graph-native clustering algorithm born from the Structure-Centric Machine Learning (SC-ML) paradigm -- a new field of unsupervised learning that replaces geometry-centric (distance-based) computati…
Dimensionality ReductionText ClusteringTopeax -- An Improved Clustering Topic Model with Density Peak Detection and Lexical-Semantic Term Importance
Text clustering is today the most popular paradigm for topic modelling, both in academia and industry. Despite clustering topic models' apparent success, we identify a number of issues in Top2Vec and BERTopic, which rema…
Text ClusteringTopic ModelsOptimized Algorithms for Text Clustering with LLM-Generated Constraints
Clustering is a fundamental tool that has garnered significant interest across a wide range of applications including text analysis. To improve clustering accuracy, many researchers have incorporated background knowledge…
Text ClusteringA Large-Language-Model Framework for Automated Humanitarian Situation Reporting
Timely and accurate situational reports are essential for humanitarian decision-making, yet current workflows remain largely manual, resource intensive, and inconsistent. We present a fully automated framework that uses …
Question GenerationText Clustering