lpq29743 / IAN

A TensorFlow implementation for "Interactive Attention Networks for Aspect-Level Sentiment Classification"

IAN

A Tensorflow implementation for "Interactive Attention Networks for Aspect-Level Sentiment Classification" (Dehong Ma, IJCAI 2017)

Quick Start

• use pip install -r requirements.txt to install required packages
• Create three empty folders: 'analysis' for saving analyzing results, 'logs' for saving experiment logs and 'models' for saving experiment models
• Download the 300-dimensional pre-trained word vectors from Glove and save it in the 'data' folder as 'data/glove.840B.300d.txt'

Source Code Tree

|--- data

|	|--- laptop

|	|--- restaurant

|	|--- data_info.txt - the preprocessing data information file

|	|--- test_data.txt - the preprocessing testing data file

|	|--- train_data.txt - the preprocessing training data file

|--- main.py

|--- model.py

|--- transfer.py - transfering the origin xml files to text files

|--- utils.py

|--- README.md

Results

Dataset	Accuracy
Laptop	70.846
Restaurant	79.107

Note: In the newest version, the results are worse than the results given above, since the code of the model is revised. I will optimize the model sooner and report the results.

Todo List

• Implementing by other deep learning frameworks
• Softmax mask
• Optimization to get better performance