Training conditional random fields using incomplete annotations

被引：0
|
作者：
Tsuboi, Yuta [1 ]
Kashima, Hisashi [1 ]
Mori, Shinsuke [2 ]
Oda, Hiroki [3 ]
Matsumoto, Yuji [4 ]
机构：
[1] Tokyo Research Laboratory, IBM Research, IBM Japan, Ltd., Yamato, Kanagawa 242-8502, Japan
[2] Academic Center for Computing and Media Studies, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
[3] Shinagawa, Tokyo, Japan
[4] Graduate School of Information Science, Nara Institute of Science and Technology, Takayama, Ikoma, Nara 630-0101, Japan
来源：
Coling 2008 - 22nd International Conference on Computational Linguistics, Proceedings of the Conference | 2008年 / 1卷
关键词：
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Conditional random field - Conditional Random Fields(CRFs) - Domain adaptation - Parameter estimation method - Part of speech tagging - Treebanks - Word segmentation
引用
下载
收藏
页码：897 / 904
相关论文
共 50 条
  • [1] A platform for semantic annotations and ontology population using conditional random fields
    Grilheres, B
    Beauce, C
    Canu, S
    Brunessaux, S
    2005 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE, PROCEEDINGS, 2005, : 790 - 793
  • [2] Training Conditional Random Fields using Virtual Evidence Boosting
    Liao, Lin
    Choudhury, Tanzeem
    Fox, Dieter
    Kautz, Henry
    20TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2007, : 2530 - 2535
  • [3] Training algorithms for hidden conditional random fields
    Mahajan, Milind
    Gunawardana, Asela
    Acero, Alex
    2006 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-13, 2006, : 273 - 276
  • [4] Margin Losses for Training Conditional Random Fields
    Ehsan Ahmadi
    Zohreh Azimifar
    Journal of Mathematical Imaging and Vision, 2016, 56 : 499 - 510
  • [5] Margin Losses for Training Conditional Random Fields
    Ahmadi, Ehsan
    Azimifar, Zohreh
    JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2016, 56 (03) : 499 - 510
  • [6] Gradient Tree Boosting for Training Conditional Random Fields
    Dietterich, Thomas G.
    Hao, Guohua
    Ashenfelter, Adam
    JOURNAL OF MACHINE LEARNING RESEARCH, 2008, 9 : 2113 - 2139
  • [7] A Bootstrapping Approach for Training a NER with Conditional Random Fields
    Teixeira, Jorge
    Sarmento, Luis
    Oliveira, Eugenio
    PROGRESS IN ARTIFICIAL INTELLIGENCE-BOOK, 2011, 7026 : 664 - +
  • [8] Gradient tree boosting for training conditional random fields
    School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR 97331, United States
    不详
    J. Mach. Learn. Res., 2008, (2113-2139):
  • [9] Training Conditional Random Fields with Multivariate Evaluation Measures
    Suzuki, Jun
    McDermott, Erik
    Isozaki, Hideki
    COLING/ACL 2006, VOLS 1 AND 2, PROCEEDINGS OF THE CONFERENCE, 2006, : 217 - 224
  • [10] Discriminative Training of Conditional Random Fields with Probably Submodular Constraints
    Maxim Berman
    Matthew B. Blaschko
    International Journal of Computer Vision, 2020, 128 : 1722 - 1735
12345