Abstractive Sentence Summarization

The Algorithm

An implementation of the Rush, Chopra, Weston work http://arxiv.org/abs/1509.00685

Our implementation differs in that we fix the context and summary token embedding matrix. Two scenarios are possible:

1. Both embedding matrices are initialised from GloVe
2. Context embedding matrix are initialised from Skip-Thought Vectors http://arxiv.org/abs/1506.06726, summary from GloVe

The Code

Helptext is available for running our code by doing:

python3 ass_train.py -h

The training corpuses are under data/. Each JSON file contains three fields title, full_text, summary. They're downloaded with scripts in download_data/.

GloVe data needs to be downloaded and unzipped under glove/. The code uses the first 10k most frequent tokens by default. To generate the embeddings for them,

cd glove
head -n 10000 glove.6B.300d.txt >glove.10k.300d.txt

SkipThoughts data needs to be downloaded to access the SkipThoughts embeddings (to be done).