APD-A tool for identifying behavioural patterns automatically from clickstream data

I-Hsien Ting; Lillian Clark; Chris Kimble; Daniel Kudenko; Peter Wright

APD-A tool for identifying behavioural patterns automatically from clickstream data

I-Hsien Ting, Lillian Clark, Chris Kimble, Daniel Kudenko, Peter Wright

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Clickstream can be a rich source of data for analysing user behaviour, but the volume of these logs makes it difficult to identify and categorise behavioural patterns. In this paper, we introduce the Automatic Pattern Discovery (APD) method, a technique for automated processing of Clickstream data to identify a user's browsing patterns. The paper also includes case study that is used to illustrate the use of the APD and to evaluate its performance.

Original language	English
Title of host publication	Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007, Pt II, Proceedings
Editors	B Apolloni, RJ Howlett, L Jain
Place of Publication	BERLIN
Publisher	Springer
Pages	66-73
Number of pages	8
ISBN (Print)	978-3-540-74826-7
Publication status	Published - 2007
Event	11th International Conference on Knowledge-Based Intelligent Informational and Engineering Systems/17th Italian Workshop on Neural Networks - Vietri sul Mare Duration: 12 Sep 2007 → 14 Sep 2007

Conference

Conference	11th International Conference on Knowledge-Based Intelligent Informational and Engineering Systems/17th Italian Workshop on Neural Networks
City	Vietri sul Mare
Period	12/09/07 → 14/09/07

Keywords

web usage mining
clickstream data
browsing behaviour
traversal pattern
NAVIGATION

Cite this

@inproceedings{5a4ee2295cca4dc5b09a802800f8c923,

title = "APD-A tool for identifying behavioural patterns automatically from clickstream data",

abstract = "Clickstream can be a rich source of data for analysing user behaviour, but the volume of these logs makes it difficult to identify and categorise behavioural patterns. In this paper, we introduce the Automatic Pattern Discovery (APD) method, a technique for automated processing of Clickstream data to identify a user's browsing patterns. The paper also includes case study that is used to illustrate the use of the APD and to evaluate its performance.",

keywords = "web usage mining, clickstream data, browsing behaviour, traversal pattern, NAVIGATION",

author = "I-Hsien Ting and Lillian Clark and Chris Kimble and Daniel Kudenko and Peter Wright",

year = "2007",

language = "English",

isbn = "978-3-540-74826-7",

pages = "66--73",

editor = "B Apolloni and RJ Howlett and L Jain",

booktitle = "Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007, Pt II, Proceedings",

publisher = "Springer",

address = "Germany",

note = "11th International Conference on Knowledge-Based Intelligent Informational and Engineering Systems/17th Italian Workshop on Neural Networks ; Conference date: 12-09-2007 Through 14-09-2007",

}

Ting, I-H, Clark, L, Kimble, C, Kudenko, D & Wright, P 2007, APD-A tool for identifying behavioural patterns automatically from clickstream data. in B Apolloni, RJ Howlett & L Jain (eds), Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007, Pt II, Proceedings. Springer, BERLIN, pp. 66-73, 11th International Conference on Knowledge-Based Intelligent Informational and Engineering Systems/17th Italian Workshop on Neural Networks, Vietri sul Mare, 12/09/07.

APD-A tool for identifying behavioural patterns automatically from clickstream data. / Ting, I-Hsien; Clark, Lillian; Kimble, Chris et al.

Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007, Pt II, Proceedings. ed. / B Apolloni; RJ Howlett; L Jain. BERLIN : Springer, 2007. p. 66-73.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - APD-A tool for identifying behavioural patterns automatically from clickstream data

AU - Ting, I-Hsien

AU - Clark, Lillian

AU - Kimble, Chris

AU - Kudenko, Daniel

AU - Wright, Peter

PY - 2007

Y1 - 2007

N2 - Clickstream can be a rich source of data for analysing user behaviour, but the volume of these logs makes it difficult to identify and categorise behavioural patterns. In this paper, we introduce the Automatic Pattern Discovery (APD) method, a technique for automated processing of Clickstream data to identify a user's browsing patterns. The paper also includes case study that is used to illustrate the use of the APD and to evaluate its performance.

AB - Clickstream can be a rich source of data for analysing user behaviour, but the volume of these logs makes it difficult to identify and categorise behavioural patterns. In this paper, we introduce the Automatic Pattern Discovery (APD) method, a technique for automated processing of Clickstream data to identify a user's browsing patterns. The paper also includes case study that is used to illustrate the use of the APD and to evaluate its performance.

KW - web usage mining

KW - clickstream data

KW - browsing behaviour

KW - traversal pattern

KW - NAVIGATION

M3 - Conference contribution

SN - 978-3-540-74826-7

SP - 66

EP - 73

BT - Knowledge-Based Intelligent Information and Engineering Systems: KES 2007 - WIRN 2007, Pt II, Proceedings

A2 - Apolloni, B

A2 - Howlett, RJ

A2 - Jain, L

PB - Springer

CY - BERLIN

T2 - 11th International Conference on Knowledge-Based Intelligent Informational and Engineering Systems/17th Italian Workshop on Neural Networks

Y2 - 12 September 2007 through 14 September 2007

ER -