## Model-based clustering and visualization of navigation patterns on a web site (2003)

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Venue: | Data Mining and Knowledge Discovery |

Citations: | 56 - 0 self |

### BibTeX

@ARTICLE{Cadez03model-basedclustering,

author = {Igor Cadez and David Heckerman and Christopher Meek and Padhraic Smyth and Steven White},

title = {Model-based clustering and visualization of navigation patterns on a web site},

journal = {Data Mining and Knowledge Discovery},

year = {2003},

pages = {399--424}

}

### Years of Citing Articles

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### Abstract

We present a new methodology for exploring and analyzing navigation patterns on a web site. The patterns that can be analyzed consist of sequences of URL categories traversed by users. In our approach, we rst partition site users into clusters such that users with similar navigation paths through the site are placed into the same cluster. Then, for each cluster, we display these paths for users within that cluster. The clustering approach weemployis model-based (as opposed to distance-based) and partitions users according to the order in which they request web pages. In particular, we cluster users by learning a mixture of rst-order Markov models using the Expectation-Maximization algorithm. The runtime of our algorithm scales linearly with the number of clusters and with the size of the data � and our implementation easily handles hundreds of thousands of user sessions in memory. In the paper, we describe the details of our method and a visualization tool based on it called WebCANVAS. We illustrate the use of our approach on user-tra c data from msnbc.com. Keywords: Model-based clustering, sequence clustering, data visualization, Internet, web 1

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1 | Cadez received a BS degree in Physics from the University of Belgrade, Yugoslavia in 1995, an MS degree in Physics from the University of California, Irvine in 1997, and a PhD in Computer Science from UC Irvine in 2002. He was a recipient of a Microsoft G - Igor |

1 | is founder and manager of the Machine Learning and Applied Statistics Group at Microsoft Research. Since 1992, he has been a Senior Researcher at Microsoft, where he has created applications including data-mining tools in SQL Server and Commerce Server, t - Heckerman |