IEICE TRANSACTIONS on Information
Using Machine Learning for Automatic Estimation of Emphases in Japanese Documents
Summary :
We propose a method for automatic emphasis estimation using conditional random fields. In our experiments, the value of F-measure obtained using our proposed method (0.31) was higher than that obtained using a random emphasis method (0.20), a method using TF-IDF (0.21), and a method based on LexRank (0.26). On the contrary, the value of F-measure of obtained using our proposed method (0.28) was slightly worse as compared with that obtained using manual estimation (0.26-0.40, with an average of 0.35).
- Publication
- IEICE TRANSACTIONS on Information Vol.E100-D No.10 pp.2669-2672
- Publication Date
- 2017/10/01
- Publicized
- 2017/07/21
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2016EDL8247
- Type of Manuscript
- LETTER
- Category
- Natural Language Processing
Authors
Masaki MURATA
Tottori University
Yuki ABE
Tottori University
Keyword
Latest Issue
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Masaki MURATA, Yuki ABE, "Using Machine Learning for Automatic Estimation of Emphases in Japanese Documents" in IEICE TRANSACTIONS on Information,
vol. E100-D, no. 10, pp. 2669-2672, October 2017, doi: 10.1587/transinf.2016EDL8247.
Abstract: We propose a method for automatic emphasis estimation using conditional random fields. In our experiments, the value of F-measure obtained using our proposed method (0.31) was higher than that obtained using a random emphasis method (0.20), a method using TF-IDF (0.21), and a method based on LexRank (0.26). On the contrary, the value of F-measure of obtained using our proposed method (0.28) was slightly worse as compared with that obtained using manual estimation (0.26-0.40, with an average of 0.35).
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2016EDL8247/_p
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@ARTICLE{e100-d_10_2669,
author={Masaki MURATA, Yuki ABE, },
journal={IEICE TRANSACTIONS on Information},
title={Using Machine Learning for Automatic Estimation of Emphases in Japanese Documents},
year={2017},
volume={E100-D},
number={10},
pages={2669-2672},
abstract={We propose a method for automatic emphasis estimation using conditional random fields. In our experiments, the value of F-measure obtained using our proposed method (0.31) was higher than that obtained using a random emphasis method (0.20), a method using TF-IDF (0.21), and a method based on LexRank (0.26). On the contrary, the value of F-measure of obtained using our proposed method (0.28) was slightly worse as compared with that obtained using manual estimation (0.26-0.40, with an average of 0.35).},
keywords={},
doi={10.1587/transinf.2016EDL8247},
ISSN={1745-1361},
month={October},}
Copy
TY - JOUR
TI - Using Machine Learning for Automatic Estimation of Emphases in Japanese Documents
T2 - IEICE TRANSACTIONS on Information
SP - 2669
EP - 2672
AU - Masaki MURATA
AU - Yuki ABE
PY - 2017
DO - 10.1587/transinf.2016EDL8247
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 10
JA - IEICE TRANSACTIONS on Information
Y1 - October 2017
AB - We propose a method for automatic emphasis estimation using conditional random fields. In our experiments, the value of F-measure obtained using our proposed method (0.31) was higher than that obtained using a random emphasis method (0.20), a method using TF-IDF (0.21), and a method based on LexRank (0.26). On the contrary, the value of F-measure of obtained using our proposed method (0.28) was slightly worse as compared with that obtained using manual estimation (0.26-0.40, with an average of 0.35).
ER -
English
