Global models of document structure using latent permutations
We present a novel Bayesian topic model for learning discourse-level document structure. Our model leverages insights from discourse theory to constrain latent topic assignments in a way that reflects the underlying organization of document topics. We propose a global model in which both topic selec...
| Үндсэн зохиолчид: | , , , |
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| Бусад зохиолчид: | |
| Формат: | Өгүүллэг |
| Хэл сонгох: | en_US |
| Хэвлэсэн: |
Association for Computational Linguistics
2010
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| Нөхцлүүд: | |
| Онлайн хандалт: | http://hdl.handle.net/1721.1/59312 https://orcid.org/0000-0002-2921-8201 https://orcid.org/0000-0002-0024-5847 |