A repository containing many components used to build and test PrivateJobMatch using Python 2.7
Thesis: https://arxiv.org/abs/1905.04564
Long-Paper @ RecSys 2019: x
- Small script to generate synthetic candidate-employer preferences using the function
createDatasets
in Dataset_Generator.py - Preferences are reasonably decided based on a utility function (assigned type).
- Specify the number of candidates and employers, n and m respectively.
- Code for simulating a job market.
- Employers offer jobs to candidates using a descending order of candidate priority, which can be inputted in the form of:
- Raw preferences (as used in today's decentralized job market).
- MMDAA match output (centralized job market).
- Code for performing LMF on a sparse dataset. See LMF_Runner.py
- Included a utility function,
sparsifyDataset
, for converting a dense dataset into a sparse dataset.
- MMDAA.py contains functions for various tasks.
setUpInputFile
will create a text file in the required format/structure for parsing when setting up the data structures (preprocessing) for running the MMDAA.- See exampleInput.txt for required preference structure.
- Takes two dense preference files (CSV format) as input. Outputs a text file.
mainRunner
loads the input text file that holds the required preference data, and runs the MMDAA. Saves the output in CSV files, as well as a text file.runMetric
is a function used to select a metric to calculate, given match outputs and preference inputs.
- A folder containing experimental results (displacement, withholdings, vacancy) in the form of spreadsheets for various datasets.