Chinese Named Entity Recognition with Inception Architecture and Weight Loss

DOI

10.2991/acaai-18.2018.29How to use a DOI?

Keywords

Named entity recognition(NER); Natural Language Processing (NLP); Chinese social media;Deep Learning

Abstract

Named Entity Recognition(NER) is a very important part of many Natural Language Processing(NLP) tasks, but the accuracy rate of NER has not reached our expectation, especially in Chinese. Therefore, we studied NER task in Chinese social media. Compared to the previous papers on this dataset, we propose a new network structure that greatly improve the recognition performance. At the same time, we noticed that the recall rate of their experimental results is much lower than the precision rate, so we also explored a method to mitigate this situation by changing the loss function. Finally, the experimental results of ours with the new loss function obtained not only higher recall rates, but also significant speedup in training phase compared to the state-of-the-art methods.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jun Zhao
AU  - Wei Fang
PY  - 2018/03
DA  - 2018/03
TI  - Chinese Named Entity Recognition with Inception Architecture and Weight Loss
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 125
EP  - 128
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.29
DO  - 10.2991/acaai-18.2018.29
ID  - Zhao2018/03
ER  -