Basic implementation of SparseSCVB0 algorithm for LDA in Rashidul Islam, and James Foulds. "Scalable Collapsed Inference for High-Dimensional Topic Models." Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). 2019.
- Julia (tested on v0.6.4.1)
- Optional Julia packages: MAT and JLD (to save the generated results)
The code is tested on windows and linux operating systems. It should work on any other platform.
The input is a single file, with one line per document where each word is separated by a space. Words in each document are represented by one-based dictionary indices. The demo is provided on NIPS corpus NIPS corpus, due to Sam Roweis. See more in data folder where NIPS.txt and NIPSdict.txt contain the corpus and dictionary, respectively.
To run SparseSCVB0 for LDA on NIPS corpus, simply run "runSparseSCVB0.jl" Julia file.
- Rashidul Islam (email: [email protected])
The code to implement SparseSCVB0 is licensed under Apache License Version 2.0.
Many part of the implementation was based on the Julia code implementing original SCVB0.