Identifying web navigation behaviour and patterns automatically from clickstream data
I. Ting, L. Clark, and C. Kimble. International Journal of Web Engineering and Technology, 5 (4):
398--398(2009)
Abstract
A user’s clickstream, such as that which is found in server-side logs, can be a rich source of data concerning the ways in which a user navigates a site, but the volume and level of detail found in these logs makes it difficult to identify and categorise specific navigational patterns. In this paper, we describe the three-step automatic pattern discovery (APD) method, a tool that utilises sequential mining to extract a user’s navigation route based on two levels of basic navigational elements. This paper contains descriptions of two studies in which the APD was used; the first makes use of APD to analyse the usage of an educational website; the second describes how APD was used to improve the design of a technical support website in a university department.
%0 Journal Article
%1 ting2009identifying
%A Ting, I Hsien
%A Clark, Lillian
%A Kimble, Chris
%D 2009
%J International Journal of Web Engineering and Technology
%K imported
%N 4
%P 398--398
%T Identifying web navigation behaviour and patterns automatically from clickstream data
%V 5
%X A user’s clickstream, such as that which is found in server-side logs, can be a rich source of data concerning the ways in which a user navigates a site, but the volume and level of detail found in these logs makes it difficult to identify and categorise specific navigational patterns. In this paper, we describe the three-step automatic pattern discovery (APD) method, a tool that utilises sequential mining to extract a user’s navigation route based on two levels of basic navigational elements. This paper contains descriptions of two studies in which the APD was used; the first makes use of APD to analyse the usage of an educational website; the second describes how APD was used to improve the design of a technical support website in a university department.
@article{ting2009identifying,
abstract = {A user’s clickstream, such as that which is found in server-side logs, can be a rich source of data concerning the ways in which a user navigates a site, but the volume and level of detail found in these logs makes it difficult to identify and categorise specific navigational patterns. In this paper, we describe the three-step automatic pattern discovery (APD) method, a tool that utilises sequential mining to extract a user’s navigation route based on two levels of basic navigational elements. This paper contains descriptions of two studies in which the APD was used; the first makes use of APD to analyse the usage of an educational website; the second describes how APD was used to improve the design of a technical support website in a university department.},
added-at = {2019-06-20T17:45:34.000+0200},
author = {Ting, I Hsien and Clark, Lillian and Kimble, Chris},
biburl = {https://www.bibsonomy.org/bibtex/2371640efcc607c63e1886392f4686a09/xckuk},
interhash = {51227cde163c93066e553a98ee6d1000},
intrahash = {371640efcc607c63e1886392f4686a09},
journal = {International Journal of Web Engineering and Technology},
keywords = {imported},
number = 4,
pages = {398--398},
timestamp = {2019-06-20T17:49:12.000+0200},
title = {Identifying web navigation behaviour and patterns automatically from clickstream data},
volume = 5,
year = 2009
}