Inter-document contextual language model

    Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

    3 Citations (Scopus)

    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 languageEnglish
    Title of host publicationThe 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2016)
    Subtitle of host publicationProceedings of the Conference, June 12-17, 2016, San Diego, California, USA
    EditorsAni Nenkova, Owen Rambow
    Place of PublicationStroudsburg, PA
    PublisherAssociation for Computational Linguistics (ACL)
    Pages762-766
    Number of pages5
    ISBN (Print)9781941643914
    Publication statusPublished - 2016
    EventNorth American Association for Computational Linguistics 2016: Human Language Technologies - Sheraton San Diego Hotel & Marina, San Diego, United States of America
    Duration: 12 Jun 201617 Jun 2016
    Conference number: 15th
    http://naacl.org/naacl-hlt-2016/

    Conference

    ConferenceNorth American Association for Computational Linguistics 2016
    Abbreviated titleNAACL HLT 2016
    CountryUnited States of America
    CitySan Diego
    Period12/06/1617/06/16
    Internet address

    Cite this

    Tran, Q. H., Zukerman, I., & Haffari, G. (2016). Inter-document contextual language model. In A. Nenkova, & O. Rambow (Eds.), 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 (pp. 762-766). Stroudsburg, PA: Association for Computational Linguistics (ACL).
    Tran, Quan Hung ; Zukerman, Ingrid ; Haffari, Gholamreza. / Inter-document contextual language model. 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. editor / Ani Nenkova ; Owen Rambow. Stroudsburg, PA : Association for Computational Linguistics (ACL), 2016. pp. 762-766
    @inproceedings{37cbce9870474ddfa3259cb04703f84e,
    title = "Inter-document contextual language model",
    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.",
    author = "Tran, {Quan Hung} and Ingrid Zukerman and Gholamreza Haffari",
    year = "2016",
    language = "English",
    isbn = "9781941643914",
    pages = "762--766",
    editor = "Ani Nenkova and Owen Rambow",
    booktitle = "The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2016)",
    publisher = "Association for Computational Linguistics (ACL)",

    }

    Tran, QH, Zukerman, I & Haffari, G 2016, Inter-document contextual language model. in A Nenkova & O Rambow (eds), 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. Association for Computational Linguistics (ACL), Stroudsburg, PA, pp. 762-766, North American Association for Computational Linguistics 2016, San Diego, United States of America, 12/06/16.

    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 proceedingConference PaperResearchpeer-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.

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    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 -

    Tran QH, Zukerman I, Haffari G. Inter-document contextual language model. In Nenkova A, Rambow O, editors, 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. Stroudsburg, PA: Association for Computational Linguistics (ACL). 2016. p. 762-766