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Text Clustering

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 3
평가표: 3
보존된 평가 기록: 34

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)

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yzh0905/pota-stc

공식 코드

Reliable Pseudo-labeling via Optimal Transport with Attention for Short Text Clustering

https://github.com/zhang-yu-wei/clusterllm

공식 코드

ClusterLLM: Large Language Models as a Guide for Text Clustering

https://github.com/SyedMuhammadFaheem/Urdu-News-Clustering

https://github.com/hadifar/stc_clustering

https://github.com/jonjoncardoso/jonjoncardoso

Very Large Language Model as a Unified Methodology of Text Mining

https://github.com/lyon-nlp/mteb-french

MTEB: Massive Text Embedding Benchmark

https://github.com/makcedward/nlpaug

Supporting Clustering with Contrastive Learning

https://github.com/wadoodabdul/clinical_ner_benchmark

MTEB: Massive Text Embedding Benchmark

https://github.com/zll17/Neural_Topic_Models

Neural Topic Modeling with Bidirectional Adversarial Training

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.