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

I. Ting; Lillian Clark; C. Kimble; D. Kudenko; Peter Wright

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

I. Ting, Lillian Clark, C. Kimble, D. Kudenko, Peter Wright

University of York

Research output: Contribution to conference › Paper › peer-review

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
Pages	66-73
Number of pages	8
Publication status	Published - 2007
Event	Knowledge-Based Intelligent Information and Engineering Systems11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks - Vietri sul Mare, Italy Duration: 12 Sept 2007 → 14 Sept 2007

Conference

Conference	Knowledge-Based Intelligent Information and Engineering Systems11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks
Country/Territory	Italy
City	Vietri sul Mare
Period	12/09/07 → 14/09/07

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Ting, I., Clark, L., Kimble, C., Kudenko, D., & Wright, P. (2007). APD-A tool for identifying behavioural patterns automatically from clickstream data. 66-73. Paper presented at Knowledge-Based Intelligent Information and Engineering Systems11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy. http://www.springerlink.com/content/3546913450q8vpx3/

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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{\textquoteright}s browsing patterns. The paper also includes case study that is used to illustrate the use of the APD and to evaluate its performance.",

author = "I. Ting and Lillian Clark and C. Kimble and D. Kudenko and Peter Wright",

year = "2007",

language = "English",

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note = "Knowledge-Based Intelligent Information and Engineering Systems11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks ; Conference date: 12-09-2007 Through 14-09-2007",

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Ting, I, Clark, L, Kimble, C, Kudenko, D & Wright, P 2007, 'APD-A tool for identifying behavioural patterns automatically from clickstream data', Paper presented at Knowledge-Based Intelligent Information and Engineering Systems11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy, 12/09/07 - 14/09/07 pp. 66-73. <http://www.springerlink.com/content/3546913450q8vpx3/>

APD-A tool for identifying behavioural patterns automatically from clickstream data. / Ting, I.; Clark, Lillian; Kimble, C. et al.
2007. 66-73 Paper presented at Knowledge-Based Intelligent Information and Engineering Systems11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks, Vietri sul Mare, Italy.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

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

AU - Ting, I.

AU - Clark, Lillian

AU - Kimble, C.

AU - Kudenko, D.

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.

M3 - Paper

SP - 66

EP - 73

T2 - Knowledge-Based Intelligent Information and Engineering Systems11th International Conference, KES 2007, XVII Italian Workshop on Neural Networks

Y2 - 12 September 2007 through 14 September 2007

ER -

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

Abstract

Conference

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