DocumentCode :
2183500
Title :
UBB mining: finding unexpected browsing behaviour in clickstream data to improve a Web site´s design
Author :
Ting, I-Hsien ; Kimble, Chris ; Kudenko, Daniel
Author_Institution :
Dept. of Comput. Sci., York Univ., UK
fYear :
2005
fDate :
19-22 Sept. 2005
Firstpage :
179
Lastpage :
185
Abstract :
This paper describes a novel Web usage mining approach to discover patterns in the navigation of Web sites known as unexpected browsing behaviours (UBBs). By reviewing these UBBs, a Web site designer can choose to modify the design of their Web site or redesign the site completely. UBB mining is based on the continuous common subsequence (CCS), a special instance of common subsequence (CS), which is used to define a set of expected routes. The predefined expected routes are then treated as rules and stored in a rule base. By using the predefined route and the UBB mining algorithm, interesting browsing behaviours can be discovered. This paper introduces the format of the expected route and describes the UBB algorithms. The paper also describes a series of experiments designed to evaluate how well UBB mining algorithms work.
Keywords :
Web design; data mining; online front-ends; UBB mining; Web site design; Web site navigation; Web usage mining; clickstream data; continuous common subsequence; pattern discovery; unexpected browsing behaviour; Algorithm design and analysis; Carbon capture and storage; Computer science; Data mining; Navigation; Sections; Web design; Web page design;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence, 2005. Proceedings. The 2005 IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2415-X
Type :
conf
DOI :
10.1109/WI.2005.153
Filename :
1517840
Link To Document :
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