Multi-Entity Aspect-Based Sentiment Analysis With Context, Entity and Aspect Memory
Authors: Jun Yang, Runqi Yang, Chongjun Wang, Junyuan Xie
AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental results show that our CEA method achieves a significant gain over several baselines, including the state-of-the-art method for the ABSA task, and their enhanced versions, on datasets for ME-ABSA and ABSA tasks. |
| Researcher Affiliation | Academia | Jun Yang, Runqi Yang, Chongjun Wang, Junyuan Xie National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China yangjunny@126.com, runqiyang@gmail.com, chjwang@nju.edu.cn, jyxie@nju.edu.cn |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks (clearly labeled algorithm sections or code-like formatted procedures). |
| Open Source Code | Yes | Code and data are available at http://www.marcpoint.com/junyang.html. |
| Open Datasets | Yes | We release our dataset, looking forward to advancing the research in fine-grained sentiment analysis. Code and data are available at http://www.marcpoint.com/junyang.html. |
| Dataset Splits | Yes | We provide a training set BC-Train for model training, a development set BC-Dev for parameter tuning and a test set BC-Test for evaluation. The statistics of our dataset are listed in Table 1. |
| Hardware Specification | Yes | Testing time is the running time on test set BC-Test on an i7-16GB-GTX1070(GPU) computer with tensorflow framework4 and batch size at testing is set to 1000 for all methods. |
| Software Dependencies | No | The paper mentions 'tensorflow framework' and 'Jieba' but does not specify their version numbers. |
| Experiment Setup | Yes | We train our model 10 iterations with a batch of 25 instances, the L2-regularization weight of 0.001, the learning rate of 0.001 for Adam optimizer. The dropout rate before LSTM and before softmax are both set to 0.5. The maximum hop count is set to 3. |