Date of Award
2010
Publication Type
Master Thesis
Degree Name
M.Sc.
Department
Computer Science
Keywords
Applied sciences
Supervisor
Christie Ezeife
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
An uncertain data sequence is a sequence of data that exist with some level of doubt or probability. Each data item in the uncertain sequence is represented with a label and probability values, referred to as existential probability, ranging from 0 to 1.
Existing algorithms are either unsuitable or inefficient for discovering frequent sequences in uncertain data. This thesis presents mining of uncertain Web sequences with a method that combines access history probabilities from several Web log sessions with features of the PLWAP web sequential miner. The method is Uncertain Position Coded Pre-order Linked Web Access Pattern (U-PLWAP) algorithm for mining frequent sequential patterns in uncertain web logs. While PLWAP only considers a session of weblogs, U-PLWAP takes more sessions of weblogs from which existential probabilities are generated. Experiments show that U-PLWAP is at least 100% faster than U-apriori, and 33% faster than UF-growth. The UF-growth algorithm also fails to take into consideration the order of the items, thereby making U-PLWAP a richer algorithm in terms of the information its result contains.
Recommended Citation
Kadri, Olalekan Habeeb, "Mining of uncertain Web log sequences with access history probabilities" (2010). Electronic Theses and Dissertations. 8058.
https://scholar.uwindsor.ca/etd/8058