ALSim is a Python library for iterative batch-mode active learning simulations.
The package code is stored under src/alsim.
The entry point is alsim.run, which takes command-line args that specify the configuration loaded.
To use it, currently alsim.paths.GIT_ROOT_DIR needs to be manually set and src/alsim/data.py needs to be updated to load the documents in the expected dictionary format from a directory called data/.
This repository was used to generate the results presented in the associated IUI conference paper. The configurations for those experiments can be found in src/alsim/config.py.
The ALSim library was solely authored by Zachary Levonian in 2021. It includes code from other MIT-licensed repositories.
The associated conference paper was submitted to IUI 2022 in September 2021 and accepted in December 2021.
Please cite the IUI conference paper if the code in this repository is useful to you in your research. See the CITATION.cff file in this repository.
Zachary Levonian, Chia-Jung Lee, Vanessa Murdock, and F. Maxwell Harper. 2022. Trade-offs in Sampling and Search for Early-stage Interactive Text Classification. In 27th International Conference on Intelligent User Interfaces (IUI ’22), March 22–25, 2022, Helsinki, Finland. ACM, New York, NY, USA. https://doi.org/10.1145/3490099.3511134