Extracting pairs of aspect and sentiment expression from Indonesian hotel reviews.

The approach is to identify all possible candidate pairs and then classify them into valid or invalid class.

.
├── ner
├── pairing
└── utility

• ner : Classify tokens whether they are aspect term, sentiment term, or not both. This is only a sandbox, we won't focus on it.
• pairing : Main module, containing file reader, feature extractor, and pair classifier.
• utility : Helper for main module.

Create directories to store data and save trained model. Put train and test dataset to data/labelled.

.
├── data
|   ├── labelled
|   |   ├── train-pair.txt
|   |   └── test-pair.txt
|   └── raw
└── model
    ├── ner
    ├── pairing
    └── utility

Then, run demo.ipynb for demonstration or any other jupyter notebook files.