GMOCAT-CODE

Official Code for paper "GMOCAT: A Graph-Enhanced Multi-Objective Method for Computerized Adaptive Testing"

requirements:

Python, PyTorch, dgl

how to run codes

We have provided the preprocessed dataset assist2009 so that we can directly run experiments on IRT with assist2009. To run GMOCAT, please run train_gcat.sh.

how to run codes from scratch

put raw data in raw_data/.
run preprocessing.py and construct_graphs.py.
run pretrain.sh.
run the selection algorithms train_gcat.sh.

CAT baselines can be found in https://github.com/bigdata-ustc/CAT, https://github.com/bigdata-ustc/NCAT and https://github.com/arghosh/BOBCAT.

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
agents		agents
baseline_log/assist2009		baseline_log/assist2009
data		data
envs		envs
function		function
graph_data/assist2009		graph_data/assist2009
models/assist2009		models/assist2009
pretrain_log/assist2009		pretrain_log/assist2009
raw_data		raw_data
.gitignore		.gitignore
README.md		README.md
construct_graphs.py		construct_graphs.py
launch_gcat.py		launch_gcat.py
preprocessing.py		preprocessing.py
pretrain.py		pretrain.py
pretrain.sh		pretrain.sh
train_gcat.sh		train_gcat.sh
util.py		util.py

justarter/GMOCAT

Folders and files

Latest commit

History

Repository files navigation

GMOCAT-CODE

requirements:

how to run codes

how to run codes from scratch

About

Resources

Stars

Watchers

Forks

Languages