<?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%">Maria Giatsoglou</style></author><author><style face="normal" font="default" size="100%">Despoina Chatzakou</style></author><author><style face="normal" font="default" size="100%">Neil Shah</style></author><author><style face="normal" font="default" size="100%">Alex Beutel</style></author><author><style face="normal" font="default" size="100%">Christos Faloutsos</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ND-SYNC: Detecting Synchronized Fraud Activities</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Knowledge Discovery and Data Mining, 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-18032-8_16</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">201â€“214</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Nick Bassiliades</style></author><author><style face="normal" font="default" size="100%">Mirjana Ivanovic</style></author><author><style face="normal" font="default" size="100%">Margita Kon-Popovska</style></author><author><style face="normal" font="default" size="100%">Yannis Manolopoulos</style></author><author><style face="normal" font="default" size="100%">Themis Palpanas</style></author><author><style face="normal" font="default" size="100%">Goce Trajcevski</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">New Trends in Database and Information Systems II - Selected papers of the 18th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events, ADBIS 2014 Ohrid, Macedonia, September 7-10, 2014 Proceedings II</style></title><secondary-title><style face="normal" font="default" size="100%">Advances in Intelligent Systems and Computing</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%"> </style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-10518-5</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><volume><style face="normal" font="default" size="100%">312</style></volume><isbn><style face="normal" font="default" size="100%">978-3-319-10517-8</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Barbara Catania</style></author><author><style face="normal" font="default" size="100%">Cerquitelli, Tania</style></author><author><style face="normal" font="default" size="100%">Chiusano, Silvia</style></author><author><style face="normal" font="default" size="100%">Guerrini, Giovanna</style></author><author><style face="normal" font="default" size="100%">Kämpf, Mirko</style></author><author><style face="normal" font="default" size="100%">Kemper, Alfons</style></author><author><style face="normal" font="default" size="100%">Novikov, Boris</style></author><author><style face="normal" font="default" size="100%">Palpanas, Themis</style></author><author><style face="normal" font="default" size="100%">Pokorny, Jaroslav</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">New Trends in Databases and Information Systems, 17th East European Conference on Advances in Databases and Information Systems</style></title><secondary-title><style face="normal" font="default" size="100%">ADBIS (2)</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Advances in Intelligent Systems and Computing</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2013</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Genoa, Italy</style></pub-location><volume><style face="normal" font="default" size="100%">241</style></volume><isbn><style face="normal" font="default" size="100%">978-3-319-01863-8</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>6</ref-type><contributors><secondary-authors><author><style face="normal" font="default" size="100%">Athena Vakali</style></author><author><style face="normal" font="default" size="100%">Jain, Lakhmi C.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">New Directions in Web Data Management 1</style></title><secondary-title><style face="normal" font="default" size="100%">New Directions in Web Data Management 1</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Studies in Computational Intelligence</style></tertiary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><volume><style face="normal" font="default" size="100%">331</style></volume><isbn><style face="normal" font="default" size="100%">978-3-642-17550-3</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">A new approach to web users clustering and validation: a divergence-based scheme</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Purpose – Web users’ clustering is an important mining task since it contributes in identifying usagepatterns, a beneficial task for a wide range of applications that rely on the web. The purpose of thispaper is to examine the usage of Kullback-Leibler (KL) divergence, an information theoretic distance,as an alternative option for measuring distances in web users clustering.Design/methodology/approach – KL-divergence is compared with other well-known distancemeasures and clustering results are evaluated using a criterion function, validity indices, andgraphical representations. Furthermore, the impact of noise (i.e. occasional or mistaken page visits) isevaluated, since it is imperative to assess whether a clustering process exhibits tolerance in noisyenvironments such as the web.Findings – The proposed KL clustering approach is of similar performance when compared withother distance measures under both synthetic and real data workloads. Moreover, imposing extranoise on real data, the approach shows minimum deterioration among most of the other conventionaldistance measures.Practical implications – The experimental results show that a probabilistic measure such asKL-divergence has proven to be quite efficient in noisy environments and thus constitute a goodalternative, the web users clustering problem.Originality/value – This work is inspired by the usage of divergence in clustering of biological dataand it is introduced by the authors in the area of web clustering. According to the experimental resultspresented in this paper, KL-divergence can be considered as a good alternative for measuringdistances in noisy environments such as the web.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</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%">Petridou, Sophia G.</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author><author><style face="normal" font="default" size="100%">Papadimitriou, Georgios I.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A new approach to web users clustering and validation: a divergence-based scheme</style></title><secondary-title><style face="normal" font="default" size="100%">IJWIS</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cluster analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Internet Data mining</style></keyword><keyword><style  face="normal" font="default" size="100%">User studies</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">5</style></volume><pages><style face="normal" font="default" size="100%">348-371</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Purpose â€“ Web usersâ€™ clustering is an important mining task since it contributes in identifying usagepatterns, a beneficial task for a wide range of applications that rely on the web. The purpose of thispaper is to examine the usage of Kullback-Leibler (KL) divergence, an information theoretic distance,as an alternative option for measuring distances in web users clustering.Design/methodology/approach â€“ KL-divergence is compared with other well-known distancemeasures and clustering results are evaluated using a criterion function, validity indices, andgraphical representations. Furthermore, the impact of noise (i.e. occasional or mistaken page visits) isevaluated, since it is imperative to assess whether a clustering process exhibits tolerance in noisyenvironments such as the web.Findings â€“ The proposed KL clustering approach is of similar performance when compared withother distance measures under both synthetic and real data workloads. Moreover, imposing extranoise on real data, the approach shows minimum deterioration among most of the other conventionaldistance measures.Practical implications â€“ The experimental results show that a probabilistic measure such asKL-divergence has proven to be quite efficient in noisy environments and thus constitute a goodalternative, the web users clustering problem.Originality/value â€“ This work is inspired by the usage of divergence in clustering of biological dataand it is introduced by the authors in the area of web clustering. According to the experimental resultspresented in this paper, KL-divergence can be considered as a good alternative for measuringdistances in noisy environments such as the web.&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%">Fortino, Giancarlo</style></author><author><style face="normal" font="default" size="100%">Mastroianni, Carlo</style></author><author><style face="normal" font="default" size="100%">Al-Mukaddim Khan Pathan</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Fortino, Giancarlo</style></author><author><style face="normal" font="default" size="100%">Mastroianni, Carlo</style></author><author><style face="normal" font="default" size="100%">Al-Mukaddim Khan Pathan</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Next generation content networks: trends and challenges</style></title><secondary-title><style face="normal" font="default" size="100%">UPGRADE-CN</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><publisher><style face="normal" font="default" size="100%">ACM</style></publisher><pages><style face="normal" font="default" size="100%">49</style></pages><isbn><style face="normal" font="default" size="100%">978-1-60558-591-8</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Theodosiou, Theodosios</style></author><author><style face="normal" font="default" size="100%">Angelis, Lefteris</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Non-linear correlation of content and metadata information extracted from biomedical article datasets</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Biomedical Informatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">41</style></volume><pages><style face="normal" font="default" size="100%">202-216</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">A New Approach to the Design of High Performance Multiple Disk Subsystems: Dynamic Load Balancing Schemes</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2000</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The performance of storage subsystems has not followed therapid improvements in processors technology, despite the increased capacityand density in storage medium. Here, we introduce a new modelbased on the idea of enhancing the I/O subsystem controller capabilitiesby dynamic load balancing on a storage subsystem of multiple disk drives.The request servicing is modified such that each request is directed to themost appropriate disk drive towards servicing performance improvement.The redirection is performed by a proposed algorithm which considersthe disk drive queues and the disk drives “popularity”. The proposed requestservicing has been simulated and the load balancing approach hasbeen shown quite effective as compared to conventional request servicing.&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%">Papadimitriou, Georgios I.</style></author><author><style face="normal" font="default" size="100%">Pomportsis, Andreas S.</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Bubak, Marian</style></author><author><style face="normal" font="default" size="100%">Afsarmanesh, Hamideh</style></author><author><style face="normal" font="default" size="100%">Williams, Roy</style></author><author><style face="normal" font="default" size="100%">Hertzberger, Louis O.</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">A New Approach to the Design of High Performance Multiple Disk Subsystems: Dynamic Load Balancing Schemes</style></title><secondary-title><style face="normal" font="default" size="100%">HPCN Europe</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%">2000</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><volume><style face="normal" font="default" size="100%">1823</style></volume><pages><style face="normal" font="default" size="100%">610-613</style></pages><isbn><style face="normal" font="default" size="100%">3-540-67553-1</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The performance of storage subsystems has not followed therapid improvements in processors technology, despite the increased capacityand density in storage medium. Here, we introduce a new modelbased on the idea of enhancing the I/O subsystem controller capabilitiesby dynamic load balancing on a storage subsystem of multiple disk drives.The request servicing is modified such that each request is directed to themost appropriate disk drive towards servicing performance improvement.The redirection is performed by a proposed algorithm which considersthe disk drive queues and the disk drives â€śpopularityâ€ť. The proposed requestservicing has been simulated and the load balancing approach hasbeen shown quite effective as compared to conventional request servicing.</style></abstract></record></records></xml>