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

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IAN

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

Quick Start

  • 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.6B.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 69.436
Restaurant 78.571

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

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  • Python 100.0%