Using Markov Model and Association Rules for Web Access Prediction
Mining user patterns of log file can provide significant and useful informative knowledge. A large amount of research has been done on trying to predict correctly the pages a user will request. This task requires the development of models that can predicts a user’s next request to a web server. In...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2006
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| Subjects: | |
| Online Access: | http://eprints.utm.my/3253/ http://eprints.utm.my/3253/1/A-04_DrSalihin-Springer_SCSS.pdf |
| _version_ | 1848890533042192384 |
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| author | Siriporn, Chimphlee Salim, Naomie Ngadiman, Mohd. Salihin Witcha, Chimphlee |
| author_facet | Siriporn, Chimphlee Salim, Naomie Ngadiman, Mohd. Salihin Witcha, Chimphlee |
| author_sort | Siriporn, Chimphlee |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | Mining user patterns of log file can provide significant and useful informative knowledge. A large amount of research has been done on trying to predict correctly the pages a user will request. This task requires the development of models that can predicts a user’s next request to a web server. In this paper, we propose a method for constructing first-order and second-order Markov models of Web site access prediction based on past visitor behavior and compare it association rules technique. This algorithm has been used to cluster similar transition behaviors for efficient used to further improve the efficiency of prediction. From this comparison we propose a best overall method and empirically test the proposed model on real web logs. |
| first_indexed | 2025-11-15T20:43:35Z |
| format | Conference or Workshop Item |
| id | utm-3253 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:43:35Z |
| publishDate | 2006 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-32532017-08-30T04:14:14Z http://eprints.utm.my/3253/ Using Markov Model and Association Rules for Web Access Prediction Siriporn, Chimphlee Salim, Naomie Ngadiman, Mohd. Salihin Witcha, Chimphlee Q Science (General) Mining user patterns of log file can provide significant and useful informative knowledge. A large amount of research has been done on trying to predict correctly the pages a user will request. This task requires the development of models that can predicts a user’s next request to a web server. In this paper, we propose a method for constructing first-order and second-order Markov models of Web site access prediction based on past visitor behavior and compare it association rules technique. This algorithm has been used to cluster similar transition behaviors for efficient used to further improve the efficiency of prediction. From this comparison we propose a best overall method and empirically test the proposed model on real web logs. 2006 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/3253/1/A-04_DrSalihin-Springer_SCSS.pdf Siriporn, Chimphlee and Salim, Naomie and Ngadiman, Mohd. Salihin and Witcha, Chimphlee (2006) Using Markov Model and Association Rules for Web Access Prediction. In: -, 2003, -. |
| spellingShingle | Q Science (General) Siriporn, Chimphlee Salim, Naomie Ngadiman, Mohd. Salihin Witcha, Chimphlee Using Markov Model and Association Rules for Web Access Prediction |
| title | Using Markov Model and Association Rules for Web Access Prediction |
| title_full | Using Markov Model and Association Rules for Web Access Prediction |
| title_fullStr | Using Markov Model and Association Rules for Web Access Prediction |
| title_full_unstemmed | Using Markov Model and Association Rules for Web Access Prediction |
| title_short | Using Markov Model and Association Rules for Web Access Prediction |
| title_sort | using markov model and association rules for web access prediction |
| topic | Q Science (General) |
| url | http://eprints.utm.my/3253/ http://eprints.utm.my/3253/1/A-04_DrSalihin-Springer_SCSS.pdf |