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[AAAI 2020] Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction

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LOTN

Codes and datasets for our AAAI 2022 paper: "Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction"

Overview

  • In tackling the problem of insufficient annotated data, we are the first to propose transferring latent opinion knowledge from resource-rich review sentiment classification datasets to the low-resource task of TOWE.
  • To transfer opinion information effectively, we propose a Latent Opinions Transfer Network (LOTN) model that obtains latent opinion words from a sentiment classification model and integrates them into TOWE via an auxiliary learning signal.

Dependencies

  • python=3.5
  • numpy=1.14.2
  • tensorflow==1.9

Usage

Step1: pretrained

sh run_pre_trained.sh

step2: transfer

  • Softmax
sh run_LOTN.sh
python eval_LOTN.py
  • CRF
sh run_LOTN.sh
python eval_LOTN_crf.py

Citation

@inproceedings{DBLP:conf/aaai/WuZDHC20,
  author    = {Zhen Wu and Fei Zhao and Xin{-}Yu Dai and Shujian Huang and Jiajun Chen},
  title     = {Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction},
  booktitle = {The Thirty-Fourth {AAAI} Conference on Artificial Intelligence, {AAAI} 2020, New York, NY, USA, February 7-12, 2020},
  pages     = {9298--9305},
  year      = {2020}
}

if you have any questions, please contact me zhaof@smail.nju.edu.cn.

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[AAAI 2020] Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction

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