ULTR_PrefElicit

Code for CONSEQUENCES'23 accepted paper titled, "A First Look at Selection Bias in Preference Elicitation for Recommendation".

Installing Conda Env for Synthetic Topic Simulation

To generate synthetic topics for items, we create a user-item graph and use graph embeddings, using BiNE method.

To run the BiNE network embedding, create an conda env using the "req_bine.txt" file provided with the repo.

$conda create -n --file req_bine.txt

Installing Conda Env for the Main code

For running the main code, create a conda env using the "req.txt" file provided with the repo.

$conda create -n --file req.txt

Steps to run the simulator:

First step is to download the dataset, from here

• download the Yahoo! R3 dataset.
• download the Coat dataset

Put them in the ./data/raw/yahoo, and ./data/raw/coat folders respectively.

The python file ./src/simulator.py has the code to generate the two fully-synthetic datasets (from coat and yahoo), and one fully-synthetic dataset.

$python src/simulator.py --data coat

The dataset is generated at line #73, #86, and #97 in the code. Following that the dataset can be used for different downstream tasks.

MAIN RUN SCRIPTS

To run the script for different datasets, run the following script

$ sbatch run_$DATASET.sh