CRF-based bibliography extraction from reference strings using a small amount of training data

Daiki Namikoshi; Manabu Ohta; Atsuhiro Takasu; Jun Adachi

doi:10.1109/ICDIM.2017.8244665

CRF-based bibliography extraction from reference strings using a small amount of training data

Daiki Namikoshi, Manabu Ohta, Atsuhiro Takasu, Jun Adachi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

The effective use of digital libraries demands maintenance of bibliographic databases. Useful bibliographic information appears in the reference fields of academic papers, so we are developing a method for automatic extraction of bibliographic information from reference strings using a conditional random field (CRF). However, at least a few hundred reference strings are necessary to learn an accurate CRF. In this paper, we propose active learning and transfer learning techniques to reduce the required training data for CRFs. We evaluate extraction accuracies and the associated training cost by experiments.

Original language	English
Title of host publication	2017 12th International Conference on Digital Information Management, ICDIM 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	59-64
Number of pages	6
ISBN (Electronic)	9781538606643
DOIs	https://doi.org/10.1109/ICDIM.2017.8244665
Publication status	Published - Jun 28 2017
Event	12th International Conference on Digital Information Management, ICDIM 2017 - Fukuoka, Japan Duration: Sep 12 2017 → Sep 14 2017

Publication series

Name	2017 12th International Conference on Digital Information Management, ICDIM 2017
Volume	2018-January

Other

Other	12th International Conference on Digital Information Management, ICDIM 2017
Country/Territory	Japan
City	Fukuoka
Period	9/12/17 → 9/14/17

Keywords

CRF
active learning
bibliography extraction
confidence measure
transfer learning

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Information Systems and Management

Access to Document

10.1109/ICDIM.2017.8244665

Cite this

Namikoshi, D., Ohta, M., Takasu, A., & Adachi, J. (2017). CRF-based bibliography extraction from reference strings using a small amount of training data. In 2017 12th International Conference on Digital Information Management, ICDIM 2017 (pp. 59-64). (2017 12th International Conference on Digital Information Management, ICDIM 2017; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDIM.2017.8244665

CRF-based bibliography extraction from reference strings using a small amount of training data. / Namikoshi, Daiki; Ohta, Manabu; Takasu, Atsuhiro et al.

2017 12th International Conference on Digital Information Management, ICDIM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 59-64 (2017 12th International Conference on Digital Information Management, ICDIM 2017; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Namikoshi, D, Ohta, M, Takasu, A & Adachi, J 2017, CRF-based bibliography extraction from reference strings using a small amount of training data. in 2017 12th International Conference on Digital Information Management, ICDIM 2017. 2017 12th International Conference on Digital Information Management, ICDIM 2017, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 59-64, 12th International Conference on Digital Information Management, ICDIM 2017, Fukuoka, Japan, 9/12/17. https://doi.org/10.1109/ICDIM.2017.8244665

Namikoshi D, Ohta M, Takasu A, Adachi J. CRF-based bibliography extraction from reference strings using a small amount of training data. In 2017 12th International Conference on Digital Information Management, ICDIM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 59-64. (2017 12th International Conference on Digital Information Management, ICDIM 2017). doi: 10.1109/ICDIM.2017.8244665

Namikoshi, Daiki ; Ohta, Manabu ; Takasu, Atsuhiro et al. / CRF-based bibliography extraction from reference strings using a small amount of training data. 2017 12th International Conference on Digital Information Management, ICDIM 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 59-64 (2017 12th International Conference on Digital Information Management, ICDIM 2017).

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abstract = "The effective use of digital libraries demands maintenance of bibliographic databases. Useful bibliographic information appears in the reference fields of academic papers, so we are developing a method for automatic extraction of bibliographic information from reference strings using a conditional random field (CRF). However, at least a few hundred reference strings are necessary to learn an accurate CRF. In this paper, we propose active learning and transfer learning techniques to reduce the required training data for CRFs. We evaluate extraction accuracies and the associated training cost by experiments.",

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CRF-based bibliography extraction from reference strings using a small amount of training data

Abstract

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Keywords

ASJC Scopus subject areas

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