Ting, Kimble and Kudenko (2005) UBB Mining: Finding Unexpected Browsing Behaviour in Clickstream Data to Improve a Web Site's Design

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UBB Mining: Finding Unexpected Browsing Behaviour in Clickstream Data to Improve a Web Site's Design

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CONTRIBUTORS:

	Author:	Ting, I-Hsien (National University of Kaohsiung)
	Author:	Kimble, Chris (University of York)
	Author:	Kudenko, Daniel

PROCEEDINGS TITLE:

The 2005 IEEE/WIC/ACM International Conference on Web Intelligence

YEAR:

2005

PUB TYPE:

Conference Paper in Proceedings

PAGES:

n/a - n/a

SUBJECT(S):

web mining, browsing behaviour

DISCIPLINE:

Computer Science

HTTP:

http://doi.ieeecomputersociety.org/10.1109/WI.2005.153

LANGUAGE:

English

PUB ID:

103-419-343 (Last edited on 2006/05/12 08:41:21 GMT-6)

SPONSOR(S):

ABSTRACT:
This paper describes a novel web usage mining approach to discover patterns in the navigation of websites known as Unexpected Browsing Behaviours (UBBs). By reviewing these UBBs, a website designer can choose to modify the design of their website 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 will introduce the format of the expected route and describe the UBB algorithms. The paper also describes a series of experiments designed to evaluate how well UBB mining algorithms work.

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