Text Clustering
37 papers with code • 3 benchmarks • 5 datasets
Grouping a set of texts in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). (Source: Adapted from Wikipedia)
Benchmarks
These leaderboards are used to track progress in Text Clustering
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Datasets
MTEB
20 Newsgroups
Most implemented papers
MTEB: Massive Text Embedding Benchmark
MTEB spans 8 embedding tasks covering a total of 58 datasets and 112 languages.
Dissimilarity Mixture Autoencoder for Deep Clustering
larajuse/DMAE
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The dissimilarity mixture autoencoder (DMAE) is a neural network model for feature-based clustering that incorporates a flexible dissimilarity function and can be integrated into any kind of deep learning architecture.
Discovering New Intents with Deep Aligned Clustering
thuiar/DeepAligned-Clustering
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In this work, we propose an effective method, Deep Aligned Clustering, to discover new intents with the aid of the limited known intent data.
Supporting Clustering with Contrastive Learning
amazon-research/sccl
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NAACL 2021
Unsupervised clustering aims at discovering the semantic categories of data according to some distance measured in the representation space.
Proposition-Level Clustering for Multi-Document Summarization
oriern/procluster
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NAACL 2022
Text clustering methods were traditionally incorporated into multi-document summarization (MDS) as a means for coping with considerable information repetition.
Clustering Urdu News Using Headlines
This paper that proposes and evaluates a new algorithm to automatically cluster Urdu news from different news agencies.
Self-Taught Convolutional Neural Networks for Short Text Clustering
jacoxu/STC2
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Short text clustering is a challenging problem due to its sparseness of text representation.
ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg"
We will first outline the motivation for this release, the plans for the future, and then give a brief overview over the new functionality in this version.
On the Use of ArXiv as a Dataset
We use this pipeline to extract and analyze a 6. 7 million edge citation graph, with an 11 billion word corpus of full-text research articles.
