OSGM

J. Kumar, S. U. Din, Q. Yang, R. Kumar and J. Shao, "An Online Semantic-Enhanced Graphical Model for Evolving Short Text Stream Clustering," in IEEE Transactions on Cybernetics, vol. 52, no. 12, pp. 13809-13820, Dec. 2022, doi: 10.1109/TCYB.2021.3108897.

• Python 3.7.x:

Example:

python main.py -d "data/Tweets-T-N" -o "result/" -lcb -stc -icf -cww -decay 0.000001 -mclus -ft 10 -invb -alpha 0.05 -beta 0.003

Example#2:

python main.py -d "data/Tweets-T-N" -o "result/" -lcb -stc -icf -cww -decay 0.000001 -mclus -ft 10 -invb

Example#3:

python main.py -d "data/Tweets-T-N" -o "result/" -lcb -stc -cww -decay 0.000001 -mclus -ft 10 -invb

Parameters Definitions:

• -icf : include inverse cluster frequency
• lcb : include cluster-based beta value
• cww : include word-to-word co-occurrence probability
• mclus : enable merging of outdated clusters
• stc : calculate probability for cluster containing at least one common term btw doc and cluster