Topic Model Learning Algorithm

A Topic Model Learning Algorithm is a Natural Language Processing Algorithm that can be trained to learn topic models.

• AKA: Topic Model Training Algorithm.
• Context:
  • It can be implemented by Topic Modeling System to solve a Topic Modeling Task.
  • It can range from being an Unsupervised Topic Model Learning Algorithm to being a Supervised Topic Learning Algorithm.
• Example(s):
  • Neural Topic Model Learning Algorithm,
  • VAE-based Topic Model Learning Algorithm,
  • SVG-based Topic Model Learning Algorithm,
  • Latent Topical Skip-Gram for Learning Topic Model and Vector Representations Algorithm,
  • ...
  • …
• Counter-Example(s):
  • Text Summarization Algorithm,
  • Text Segmentation Algorithm,
  • Text Extraction Algorithm.
• See: Topic Model, Language Model, Variational Autoencoder, Latent Semantic Analysis Algorithm.

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References

2019

• (Gui et al., 2019) ⇒ Lin Gui, Jia Leng, Gabriele Pergola, Yu Zhou, Ruifeng Xu, and Yulan He (2019, November). "Neural Topic Model with Reinforcement Learning". In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP 2019).

2017

• (Law et al., 2017) ⇒ Jarvan Law, Hankz Hankui Zhuo, Junhua He, and Erhu Rong (2017). "LTSG: Latent Topical Skip-Gram for Mutually Learning Topic Model and Vector Representations". In: arXiv:1702.07117.

2012

• (Arora et al., 2012) ⇒ Sanjeev Arora, Rong Ge, and Ankur Moitra (2012, October). "Learning Topic Models - Going beyond SVD". In: 2012 IEEE 53rd annual symposium on foundations of computer science (pp. 1-10). IEEE.

2007

• (Steyvers & Griffiths, 2007) ⇒ Mark Steyvers, and Tom Griffiths. (2007). “Probabilistic Topic Models.” In: (Landauer et al., 2007).

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