<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Vassiliki A. Koutsonikola</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author><author><style face="normal" font="default" size="100%">Giannakidou, Eirini</style></author><author><style face="normal" font="default" size="100%">Yiannis Kompatsiaris</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Vossen, Gottfried</style></author><author><style face="normal" font="default" size="100%">Long, Darrell D. E.</style></author><author><style face="normal" font="default" size="100%">Yu, Jeffrey Xu</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Clustering of Social Tagging System Users: A Topic and Time Based Approach</style></title><secondary-title><style face="normal" font="default" size="100%">WISE</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Social tagging systems</style></keyword><keyword><style  face="normal" font="default" size="100%">time</style></keyword><keyword><style  face="normal" font="default" size="100%">topic</style></keyword><keyword><style  face="normal" font="default" size="100%">user clustering</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><volume><style face="normal" font="default" size="100%">5802</style></volume><pages><style face="normal" font="default" size="100%">75-86</style></pages><isbn><style face="normal" font="default" size="100%">978-3-642-04408-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Under Social Tagging Systems, a typical Web 2.0 application,users label digital data sources by using freely chosen textual descriptions(tags). Mining tag information reveals the topic-domain ofusers interests and significantly contributes in a profile construction process.In this paper we propose a clustering framework which groups usersaccording to their preferred topics and the time locality of their taggingactivity. Experimental results demonstrate the efficiency of the proposedapproach which results in more enriched time-aware users profiles.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Athena Vakali</style></author><author><style face="normal" font="default" size="100%">Manolopoulos, Yannis</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Litwin, Witold</style></author><author><style face="normal" font="default" size="100%">Morzy, Tadeusz</style></author><author><style face="normal" font="default" size="100%">Vossen, Gottfried</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Replication in Mirrored Disk Systems</style></title><secondary-title><style face="normal" font="default" size="100%">ADBIS</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Lecture Notes in Computer Science</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">1998</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><volume><style face="normal" font="default" size="100%">1475</style></volume><pages><style face="normal" font="default" size="100%">224-235</style></pages><isbn><style face="normal" font="default" size="100%">3-540-64924-7</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper we study data replication in a mirrored disk system.Free disk space is exploited by keeping replicas of specific cylindersat appropriate disk locations. Assuming an organ-pipe arrangement wecalculate the expected seek distance by varying the probability cylinderaccess under different distributions. Also, analytic formulae are derivedfor the expected seek distance under replication and comparison with theconventional (without replication) mirrored disk system is performed.</style></abstract></record></records></xml>