TY - GEN
T1 - Web access path prediction using fuzzy case based reasoning
AU - Shiu, Chi Keung Simon
AU - Wong, Cody K.P.
PY - 2005/12/1
Y1 - 2005/12/1
N2 - In this paper, a fuzzy case based reasoning approach to Web access path prediction is developed and tested. It is based on the assumption that new user's access patterns can be predicted by referencing to the behaviors of similar Web users in the past. This method has three phases. Firstly, a Web case base is constructed from the Web log data. This includes the pre-processing and cleaning of the Web log data so that a suitable format is developed. Secondly, contextual information is extracted from the Web pages, and this information is used to develop a similarity measurement between Web pages. This information is added to the Web case base. Finally, fuzzy association rule mining is used to discover the relationship between the browsing behavior (user navigations) and the Web contents using the Web case base. A set of predictive cases from the Web case base is then selected for the access path prediction. From the experimental evaluation, our approach has demonstrated better prediction accuracy than the existing approaches.
AB - In this paper, a fuzzy case based reasoning approach to Web access path prediction is developed and tested. It is based on the assumption that new user's access patterns can be predicted by referencing to the behaviors of similar Web users in the past. This method has three phases. Firstly, a Web case base is constructed from the Web log data. This includes the pre-processing and cleaning of the Web log data so that a suitable format is developed. Secondly, contextual information is extracted from the Web pages, and this information is used to develop a similarity measurement between Web pages. This information is added to the Web case base. Finally, fuzzy association rule mining is used to discover the relationship between the browsing behavior (user navigations) and the Web contents using the Web case base. A set of predictive cases from the Web case base is then selected for the access path prediction. From the experimental evaluation, our approach has demonstrated better prediction accuracy than the existing approaches.
UR - http://www.scopus.com/inward/record.url?scp=33745295288&partnerID=8YFLogxK
M3 - Conference article published in proceeding or book
SN - 3540288961
SN - 9783540288961
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 135
EP - 140
BT - Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings
T2 - 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005
Y2 - 14 September 2005 through 16 September 2005
ER -