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Named entity recognition using a modified Pegasos algorithm

Published: 24 October 2011 Publication History

Abstract

In this paper, we describe a named entity recognition using a modified Pegasos algorithm for structural SVMs. We show the modified Pegasos algorithm significantly outperformed CRFs and the training time for the modified Pegasos algorithm is reduced 17-26 times compared to CRFs.

References

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Daniel M. Bikel, Scott Miller, Richard Schwartz and Ralph Weischedel. 1997. Nymble: a High-Performance Learning Name-finder. In Proc. Conference on Applied Natural Language Processing, pp.194--201.
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Andrew Borthwick, John Sterling, Eugene Agichtein and Ralph Grishman. 1998. NYU: Description of the MENE Named Entity System as used in MUC-7. In Proc. Seventh Message Understanding Conference.
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Masayuki Asahara and Yuji Matsumoto. 2003. Japanese Named Entity Extraction with Redundant Morphological Analysis. In Proc. Human Language Technology conference, pp.8--15.
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Andrew McCallum and Wei Li. 2003. Early Results for Named Entity Recognition with Conditional Random Fields, Features Induction and Web-Enhanced Lexicons. In Proc. Conference on Computational Natural Language Learning, pp.188--191.
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Ioannis Tsochantaridis, Thomas Hofmann, Thorsten Joachims and Yasemin Altun. 2004. Support Vector Machine Learning for Interdependent and Structured Output Spaces. In Proc. International Conference on Machine Learning.
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Thorsten Joachims, Thomas Finley and Chun-Nam John Yu. 2009. Cutting-Plane Training of Structural SVMs. Machine Learning, vol. 77, no. 1., pp.27--59.
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Changki Lee and Myung-Gil Jang. 2009. Fast Training of Structured SVM Using Fixed-Threshold Sequential Minimal Optimization. ETRI Journal, vol. 31, no. 2, pp.121--128.
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Shai Shalev-Shwartz, Yoram Singer and Nathan Srebro. 2007. Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In Proc. International Conference on Machine Learning, pp.807--814.
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Leon Bottou and Olivier Bousquet. 2008. The Tradeoffs of Large Scale learning. In Proc. Advances in Neural Information Processing Systems.
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Changki Lee and Myung-Gil Jang. 2010. A Modified Fixed-Threshold SMO for 1-Slack Structural SVMs. ETRI Journal, vol. 32, no. 1, pp.120--128.
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Changki Lee, Soojong Lim and Myung-Gil Jang. 2010. Large-Margin Training of Dependency Parsers Using Pegasos Algorithm. ETRI Journal, vol. 32, no. 3, pp.486--489.
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Changki Lee and Myung-Gil Jang. 2011. A Prior Model of Structural SVMs for Domain Adaptation. ETRI Journal, (in press).

Cited By

View all
  • (2018)A primal sub-gradient method for structured classification with the averaged sum lossInternational Journal of Applied Mathematics and Computer Science10.2478/amcs-2014-006724:4(917-930)Online publication date: 15-Dec-2018
  • (2017)LSTM-CRF Models for Named Entity RecognitionIEICE Transactions on Information and Systems10.1587/transinf.2016EDP7179E100.D:4(882-887)Online publication date: 2017
  • (2017)Answer ranking based on named entity types for question answeringProceedings of the 11th International Conference on Ubiquitous Information Management and Communication10.1145/3022227.3022297(1-4)Online publication date: 5-Jan-2017
  • Show More Cited By

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    cover image ACM Conferences
    CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
    October 2011
    2712 pages
    ISBN:9781450307178
    DOI:10.1145/2063576
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 24 October 2011

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    Author Tags

    1. modified pegasos algorithm
    2. named entity recognition

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    Cited By

    View all
    • (2018)A primal sub-gradient method for structured classification with the averaged sum lossInternational Journal of Applied Mathematics and Computer Science10.2478/amcs-2014-006724:4(917-930)Online publication date: 15-Dec-2018
    • (2017)LSTM-CRF Models for Named Entity RecognitionIEICE Transactions on Information and Systems10.1587/transinf.2016EDP7179E100.D:4(882-887)Online publication date: 2017
    • (2017)Answer ranking based on named entity types for question answeringProceedings of the 11th International Conference on Ubiquitous Information Management and Communication10.1145/3022227.3022297(1-4)Online publication date: 5-Jan-2017
    • (2017)Constructing a paraphrase database for agglutinative languagesData & Knowledge Engineering10.1016/j.datak.2017.07.007Online publication date: Jul-2017
    • (2016)A semantic annotation framework for scientific publicationsQuality & Quantity10.1007/s11135-016-0369-351:3(1009-1025)Online publication date: 11-Jun-2016
    • (2015)DASyR(IR) - document analysis system for systematic reviews (in Information Retrieval)Proceedings of the 2015 13th International Conference on Document Analysis and Recognition (ICDAR)10.1109/ICDAR.2015.7333830(591-595)Online publication date: 23-Aug-2015

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