Text Embedding-based Clustering Algorithm

A Text Embedding-based Clustering Algorithm is a text clustering algorithm that makes use of text embeddings.

• See: Text Embedding Algorithm.

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References

2022

• (Subakti et al., 2022) ⇒ Alvin Subakti, Hendri Murfi, and Nora Hariadi. (2022). “The Performance of BERT As Data Representation of Text Clustering.” Journal of big Data, 9(1).

2020

• (Kim, Yoon et al., 2020) ⇒ Jaeyoung Kim, Janghyeok Yoon, Eunjeong Park, and Sungchul Choi. (2020). “Patent Document Clustering with Deep Embeddings.” In: Scientometrics, 123. doi:10.1007/s11192-020-03396-7
  • NOTES:
    • It proposes a method for automatically clustering patent documents using deep learning techniques.
    • It uses a neural embedding approach called Doc2Vec to convert the text of patent abstracts into embedding vectors.

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