View Item 

Alternative approach to tree-structured web log representation and mining

Access Status
Open access
Authors
Hadzic, Fedja
Hecker, Michael
Date
2011
Type
Conference Paper

Metadata
Show full item record
Citation
Hadzic, F. and Hecker, M. 2011. Alternative approach to tree-structured web log representation and mining, in Mohand-Saïd Hacid (ed), IEEE/WIC/ACM International Conference on Web Intelligence (WI 2011), Aug 22 2011. Lyon, France: IEEE Computer Society
Source Title
Proceedings of the IEEE/WIC/ACM international conference on web intelligence (WI 2011)
Source Conference
IEEE/WIC/ACM International Conference on Web Intelligence (WI 2011)
DOI
School
Digital Ecosystems and Business Intelligence Institute (DEBII)
Remarks

© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

URI
Collection
Abstract

More recent approaches to web log data representation aim to capture the user navigational patterns with respect to the overall structure of the web site. One such representation is tree-structured log files which is the focus of this work. Most existing methods for analyzing such data are based on the use of frequent subtree mining techniques to extract frequent user activity and navigational paths. In this paper we evaluate the use of other standard data mining techniques enabled by a recently proposed structure preserving flat data representation for tree-structured data. The initially proposed framework was adjusted to better suit the web log mining task. Experimental evaluation is performed on two real world web log datasets and comparisons are made with an existing state-of-the art classifier for tree-structured data. The results show the great potential of the method in enabling the application of a wider range of data mining/analysis techniques to tree-structured web log data.