Khalil, Faten and Wang, Hua and Li, Jiuyong (2007) Integrating Markov Model with clustering for predicting web page accesses. In: 13th Australasian World Wide Web Conference (AusWeb 2007), 30 June - 4 July 2007, Coffs Harbour, Australia.
Metadata
| HTML Citation | EndNote | Dublin Core | Reference Manager |
This is the latest version of this eprint.
Full text available as:
![[img]](http://eprints.usq.edu.au/style/images/fileicons/application_pdf.png)
| PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 226Kb |
Official URL: http://eventseer.net/event/2243/
Abstract
[Abstract]: Predicting the next page to be accessed by Web users has attracted a large amount of research work lately due to the positive impact of such prediction on different areas of Web based applications. One major technique applied for this intention is Markov model. Low order Markov models are coupled with low accuracy, whereas high order Markov models are associated with high state space complexity. This paper involves incorporating clustering techniques by dividing pre-processed data into meaningful clusters then performing low order Markov models to each cluster instead of the whole data sets. Different distance measures of k-means clustering algorithm are examined in order to find an optimal one. Experiments reveal that clustering of Web documents according to Web services improves the low order Markov models accuracy.
| Item Type: | Conference or Workshop Item (DEST Category E) (Paper) |
|---|---|
| Additional Information: | Deposited in accordance with the copyright policy of the publisher. |
| Uncontrolled Keywords: | web page prediction; accuracy |
| Subjects: | 280000 Information, Computing and Communication Sciences |
| ID Code: | 4026 |
| Deposited By: | Dr Hua Wang |
| Deposited On: | 31 Mar 2008 14:13 |
| Last Modified: | 06 Nov 2008 14:31 |
Available Versions of this Item
- Integrating recommendation models for improved web page prediction accuracy. (deposited 19 Feb 2008 12:58)
- Integrating Markov Model with clustering for predicting web page accesses. (deposited 31 Mar 2008 14:13) [Currently Displayed]
Archive Staff Only: edit this record
