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20032005
most citedA Dynamic Clustering-Based Markov Model for Web Usage Mining

27 citations · 40 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IR2005

Methods for comparing rankings of search engine results

Judit Bar-Ilan, Mazlita Mat-Hassan, Mark Levene

In this paper we present a number of measures that compare rankings of search engine results. We apply these measures to five queries that were monitored daily for two periods of a…

physics.soc-ph2005

A Model for Collaboration Networks Giving Rise to a Power Law Distribution with an Exponential Cutoff

Trevor Fenner, Mark Levene, George Loizou

Recently several authors have proposed stochastic evolutionary models for the growth of complex networks that give rise to power-law distributions. These models are based on the no…

cs.AI20057 cited

A Suffix Tree Approach to Email Filtering

Rajesh M. Pampapathi, Boris Mirkin, Mark Levene

We present an approach to email filtering based on the suffix tree data structure. A method for the scoring of emails using the suffix tree is developed and a number of scoring and…

cs.AI2004

Ranking Pages by Topology and Popularity within Web Sites

Jose Borges, Mark Levene

We compare two link analysis ranking methods of web pages in a site. The first, called Site Rank, is an adaptation of PageRank to the granularity of a web site and the second, call…

cs.IR200427 cited

A Dynamic Clustering-Based Markov Model for Web Usage Mining

José Borges, Mark Levene

Markov models have been widely utilized for modelling user web navigation behaviour. In this work we propose a dynamic clustering-based method to increase a Markov model's accuracy…

cond-mat2003

On the economy of web links: Simulating the exchange process

Boris Galitsky, Mark Levene

In the modern web economy hyperlinks have already attained monetary value as incoming links to a web site can increase its visibility on major search engines. Thus links can be vie…