jaykumarr / eindm

EINDM

J. Kumar, J. Shao, R. Kumar, S. U. Din, C. B. Mawuli, and Q. Yang, and , "A Context-enhanced Dirichlet Model for Online Clustering in Short Text Streams," in Expert Systems with Applications, vol. XX, pp. xxx-xxx, Apr. 2023.

• Python 3.7.x:

Example:

python main.py -d "data/Tweets-T-N" -o "results/" -ws -icf -stc -cww -lcb -mclus -alpha 0.04 -beta 5e-4 -decay 6e-6 -epb 500 -eps 30 -epi 60 -gs

Parameters Definitions:

• -d : dataset directory
• -ws : include word specificity
• -icf : include inverse cluster frequency
• -stc : calculate probability for cluster containing at least one common term btw doc and cluster
• -cww : include word-to-word co-occurrence probability
• -lcb : include cluster-based beta value
• -mclus : enable merging of outdated clusters
• -alpha : Alpha concentration parameter
• -beta : beta parameter
• -decay : exponential decay
• -epb : queue size
• -eps : episodic inference samples
• -epi : episodic inference interval
• -gs : generate summary