A Language Model Sensitive to Discourse Context
- The paper proposes a meta language model that can dynamically incorporate the influence of wider discourse context. The model provides a conditional probability in forms of P (text|context), where the context can be arbitrary length of text, and is used to influence the probability distribution over documents. A preliminary evaluation using a 3-gram model as the base language model shows significant reductions in perplexity by incorporating discourse context.
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Main Conference Proceedings of the 12th Konvens 2014
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| Author: | Tae-Gil Noh, Sebastian Padó |
|---|---|
| URN: | https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-2822 |
| Parent Title (English): | Proceedings of the 12th edition of the KONVENS conference |
| Document Type: | Conference Proceeding |
| Language: | English |
| Date of Publication (online): | 2014/10/23 |
| Release Date: | 2014/10/23 |
| Tag: | Statistische Methoden Machine Learning; Statistical Methods |
| GND Keyword: | Maschinelles Lernen |
| First Page: | 201 |
| Last Page: | 206 |
| PPN: | Link zum Katalog |
| Institutes: | Fachbereich III / Informationswissenschaft und Sprachtechnologie |
| DDC classes: | 400 Sprache / 400 Sprache, Linguistik |
| Collections: | KONVENS 2014 / Proceedings of the 12th KONVENS 2014 |
| Licence (German): |  Creative Commons - Namensnennung 3.0 |
