Abstract
In this paper, we examine the impact of employing contextual, structural information from a tree-structured document set to derive a language model. Our results show that this information significantly improves the accuracy of the resultant model.
| Original language | English |
|---|---|
| Title of host publication | The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2016) |
| Subtitle of host publication | Proceedings of the Conference, June 12-17, 2016, San Diego, California, USA |
| Editors | Ani Nenkova, Owen Rambow |
| Place of Publication | Stroudsburg, PA |
| Publisher | Association for Computational Linguistics (ACL) |
| Pages | 762-766 |
| Number of pages | 5 |
| ISBN (Print) | 9781941643914 |
| Publication status | Published - 2016 |
| Event | North American Association for Computational Linguistics 2016: Human Language Technologies - Sheraton San Diego Hotel & Marina, San Diego, United States of America Duration: 12 Jun 2016 → 17 Jun 2016 Conference number: 15th http://naacl.org/naacl-hlt-2016/ |
Conference
| Conference | North American Association for Computational Linguistics 2016 |
|---|---|
| Abbreviated title | NAACL HLT 2016 |
| Country | United States of America |
| City | San Diego |
| Period | 12/06/16 → 17/06/16 |
| Internet address |
Cite this
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Inter-document contextual language model. / Tran, Quan Hung; Zukerman, Ingrid; Haffari, Gholamreza.
The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2016): Proceedings of the Conference, June 12-17, 2016, San Diego, California, USA. ed. / Ani Nenkova; Owen Rambow. Stroudsburg, PA : Association for Computational Linguistics (ACL), 2016. p. 762-766.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Inter-document contextual language model
AU - Tran, Quan Hung
AU - Zukerman, Ingrid
AU - Haffari, Gholamreza
PY - 2016
Y1 - 2016
N2 - In this paper, we examine the impact of employing contextual, structural information from a tree-structured document set to derive a language model. Our results show that this information significantly improves the accuracy of the resultant model.
AB - In this paper, we examine the impact of employing contextual, structural information from a tree-structured document set to derive a language model. Our results show that this information significantly improves the accuracy of the resultant model.
UR - http://www.scopus.com/inward/record.url?scp=84994153834&partnerID=8YFLogxK
UR - http://naacl.org/naacl-hlt-2016/
M3 - Conference Paper
SN - 9781941643914
SP - 762
EP - 766
BT - The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2016)
A2 - Nenkova, Ani
A2 - Rambow, Owen
PB - Association for Computational Linguistics (ACL)
CY - Stroudsburg, PA
ER -