@inproceedings{312274,
author = {Bing Liu and Wynne Hsu and Yiming Ma},
title = {Mining association rules with multiple minimum supports},
booktitle = {KDD '99: Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining},
year = {1999},
isbn = {1-58113-143-7},
pages = {337--341},
location = {San Diego, California, United States},
doi = {http://doi.acm.org/10.1145/312129.312274},
publisher = {ACM Press},
address = {New York, NY, USA},
} Motivation: To address the large set finding problem caused by treating all item as of similar frequency.
Contributions:
1) Systematically stated why applying a universal minimum support value is problematic.
2) Raised algorithm MSapriori to address this problem.
Methods:
Followed apriori, but for level 2 sets are generated differently, additionally, the pruning is more restricted. ( I think the key equation cross the whole paper is : if c(1) in s or c(2)=c(1)..... ).
Discussions:
MSapriori is a neat algorithm. Also, when apply this on table datasets, the form is a bit different.
