UBB mining: Finding Unexpected Browsing Behaviour in clickstream data to improve a web site's design
I. Ting, C. Kimble, und D. Kudenko. Proceedings - 2005 IEEE/WIC/ACM InternationalConference on Web Intelligence, WI 2005, 2005, Seite 179--185. (2005)
Zusammenfassung
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.
%0 Conference Paper
%1 ting2005mining
%A Ting, I. Hsien
%A Kimble, Chris
%A Kudenko, Daniel
%B Proceedings - 2005 IEEE/WIC/ACM InternationalConference on Web Intelligence, WI 2005
%D 2005
%K imported
%P 179--185
%T UBB mining: Finding Unexpected Browsing Behaviour in clickstream data to improve a web site's design
%V 2005
%X 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.
@inproceedings{ting2005mining,
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.},
added-at = {2019-06-20T17:45:34.000+0200},
author = {Ting, I. Hsien and Kimble, Chris and Kudenko, Daniel},
biburl = {https://www.bibsonomy.org/bibtex/2fc827e8ad186028057c280cacaff5279/xckuk},
booktitle = {Proceedings - 2005 {IEEE}/{WIC}/{ACM} {InternationalConference} on {Web} {Intelligence}, {WI} 2005},
interhash = {af991f9ffb0de6acb9f4bf1e17f6dff4},
intrahash = {fc827e8ad186028057c280cacaff5279},
keywords = {imported},
pages = {179--185},
timestamp = {2019-06-20T17:49:12.000+0200},
title = {{UBB} mining: {Finding} {Unexpected} {Browsing} {Behaviour} in clickstream data to improve a web site's design},
volume = 2005,
year = 2005
}