A biterm topic model for short texts

Xiaohui Yan, Jiafeng Guo, Yanyan Lan et al., 2013. Proceedings of the 22nd international conference on World Wide Web.

Proposes the biterm topic model for short texts, which learns topics from word pairs across the whole corpus instead of from co-occurrence within each short document.

Voynich ManuscriptArticledoi: 10.1145/2488388.2488514Checked against the original0

What it's used for here

The inductive-methods survey proposes it for finding topic shifts within single lines of the Voynich text.

Cited by on this site 1 record

1 methods surveys

Inductive methods

SRC

Cite it

Yan, X., Guo, J., Lan, Y., & Cheng, X. (2013). A biterm topic model for short texts. Proceedings of the 22nd international conference on World Wide Web. https://doi.org/10.1145/2488388.2488514

@article{yan2013biterm,
  author = {Yan, Xiaohui and Guo, Jiafeng and Lan, Yanyan and Cheng, Xueqi},
  title = {A biterm topic model for short texts},
  journal = {Proceedings of the 22nd international conference on World Wide Web},
  year = {2013},
  doi = {10.1145/2488388.2488514},
  url = {https://doi.org/10.1145/2488388.2488514}
}

TY  - JOUR
TI  - A biterm topic model for short texts
AU  - Yan, Xiaohui
AU  - Guo, Jiafeng
AU  - Lan, Yanyan
AU  - Cheng, Xueqi
PY  - 2013
JO  - Proceedings of the 22nd international conference on World Wide Web
DO  - 10.1145/2488388.2488514
UR  - https://doi.org/10.1145/2488388.2488514
ER  -

Yan, Xiaohui et al.. “A biterm topic model for short texts.” Proceedings of the 22nd international conference on World Wide Web (2013). https://doi.org/10.1145/2488388.2488514.