Skip to content

Latest commit

 

History

History
34 lines (25 loc) · 1.4 KB

File metadata and controls

34 lines (25 loc) · 1.4 KB

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

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