Code and data for paper "Dialog Intent Induction with Deep Multi-View Clustering", Hugh Perkins and Yi Yang, 2019, to appear in EMNLP 2019.

Data is available in the sub-directory data, with a specific LICENSE file.

Pre-requisites for use

• decompress the .bz2 files in datafolder
• download http://nlp.stanford.edu/data/glove.840B.300d.zip, and unzip glove.840B.300d.txt into data folder

To run AV-Kmeans

• run one of:

# no pre-training
python train.py --pre-epoch 0 --data-path data/airlines_processed.csv --num-epochs 50 --view1-col first_utterance --view2-col context

# ae pre-training
python train.py --pre-model ae --pre-epoch 20 --data-path data/airlines_processed.csv --num-epochs 50 --view1-col first_utterance --view2-col context

# qt pre-training
python train.py --pre-model qt --pre-epoch 10 --data-path data/airlines_processed.csv --num-epochs 50 --view1-col first_utterance --view2-col context

• to train on askubuntu, replace airlines with askubuntu in the above command-lines

To run k-means baseline

• for qt pretraining run:

python train_qt.py --data-path  data/airlines_processed.csv --pre-epoch 10 --view1-col first_utterance --view2-col context --scenarios view1

• to train on askubuntu, replace airlines with askubuntu in the above command-line