Mining Uncertain Web Log Sequences with Access History Probabilities
Document Type
Conference Paper
Publication Date
2011
Publication Title
Proceedings of the 2011 ACM Symposium on Applied Computing
First Page
1059
Last Page
1060
Abstract
This paper proposes (1) modeling uncertainty in web log sequences using the most recent periodic web log which attaches computed existential probabilities between 0 and 1, to events in the sequences, (2) using the newly proposed uncertain PLWAP web sequential miner for these uncertain access sequences. While PLWAP only considers a session of web logs, U-PLWAP takes more sessions of web logs from which existential probabilities are generated and there is the need to traverse each suffix tree from the root in order to scan for existential probabilities of items already found along the path. Experiments show that U-PLWAP is faster than U-Apriori, and UF-growth.
DOI
10.1145/1982185.1982417
Recommended Citation
Kadri, O. and Ezeife, C. I.. (2011). Mining Uncertain Web Log Sequences with Access History Probabilities. Proceedings of the 2011 ACM Symposium on Applied Computing, 1059-1060.
https://scholar.uwindsor.ca/computersciencepub/42