<?xml version="1.0" encoding="UTF-8"?><xml><records><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%">Mohamed Reda Bouadjenek</style></author><author><style face="normal" font="default" size="100%">Hakim Hacid</style></author><author><style face="normal" font="default" size="100%">Mokrane Bouzeghoub</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%">PerSaDoR: Personalized social document representation for improving web search</style></title><secondary-title><style face="normal" font="default" size="100%">Information Sciences</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Social recommendation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.sciencedirect.com/science/article/pii/S0020025516305278</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">369</style></volume><pages><style face="normal" font="default" size="100%">614 - 633</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Abstract In this paper, we discuss a contribution towards the integration of social information in the index structure of an {IR} system. Since each user has his/her own understanding and point of view of a given document, we propose an approach in which the index model provides a Personalized Social Document Representation (PerSaDoR) of each document per user based on his/her activities in a social tagging system. The proposed approach relies on matrix factorization to compute the PerSaDoR of documents that match a query, at query time. The complexity analysis shows that our approach scales linearly with the number of documents that match the query, and thus, it can scale to very large datasets. PerSaDoR has been also intensively evaluated by an offline study and by a user survey operated on a large public dataset from delicious showing significant benefits for personalized search compared to state of the art methods.&lt;/p&gt;
</style></abstract></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%">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%">Proceedings of the 4th Workshop on the Use of P2P, GRID and Agents for the Development of Content Networks, UPGRADE-CNâ€™09, jointly held with the 18th International Symposium on High-Performance Distributed Computing (HPDC-18 2009), 10 June 2009, Ga</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><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%">Sidiropoulos, Antonis</style></author><author><style face="normal" font="default" size="100%">Pallis, George</style></author><author><style face="normal" font="default" size="100%">Katsaros, Dimitrios</style></author><author><style face="normal" font="default" size="100%">Stamos, Konstantinos</style></author><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></contributors><titles><title><style face="normal" font="default" size="100%">Prefetching in Content Distribution Networks via Web Communities Identification and Outsourcing</style></title><secondary-title><style face="normal" font="default" size="100%">World Wide Web</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%">11</style></volume><pages><style face="normal" font="default" size="100%">39-70</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%">Partial Match Retrieval in Two-headed Disks</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2006</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 a disk with two heads per surface separatedby a fixed number of cylinders is examined. We derive the probabilitydistribution of arm stops, the expected number of stops as well asthe expected number of cylinder clusters, i.e. the number of sets of consecutivecompound cylinders. In comparison with a single-headed disk,it is shown that the performance gain may reach 50% on the average.&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%">Moussiades, 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%">PDetect: A Clustering Approach for Detecting Plagiarism in Source Code Datasets</style></title><secondary-title><style face="normal" font="default" size="100%">Comput. J.</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2005</style></year></dates><number><style face="normal" font="default" size="100%">6</style></number><volume><style face="normal" font="default" size="100%">48</style></volume><pages><style face="normal" font="default" size="100%">651-661</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 Probabilistic Validation Algorithm for Web Users’ Clusters</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2004</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;– Cluster analysis is one of the most importantaspects in the data mining process for discovering groupsand identifying interesting distributions or patterns overthe considered data sets. In the context of Web datamining, model-based clustering algorithms are often usedto cluster similar users’ sessions in order to determineWebsite access behaviors. An important issue in clusteranalysis is the evaluation of clustering results to find thepartitioning that best fits the underlying data. In thispaper, we present a novel validation technique for modelbasedclustering approaches.&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%">Pallis, George</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><author><style face="normal" font="default" size="100%">Pokorny, Jaroslav</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A probabilistic validation algorithm for Web users’ clusters</style></title><secondary-title><style face="normal" font="default" size="100%">SMC (5)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2004</style></year></dates><publisher><style face="normal" font="default" size="100%">IEEE</style></publisher><pages><style face="normal" font="default" size="100%">4129-4134</style></pages><isbn><style face="normal" font="default" size="100%">0-7803-8566-7</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%">Athena Vakali</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Proxy Cache Replacement Algorithms: A History-Based Approach</style></title><secondary-title><style face="normal" font="default" size="100%">World Wide Web</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2001</style></year></dates><number><style face="normal" font="default" size="100%">4</style></number><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">277-298</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>17</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></contributors><titles><title><style face="normal" font="default" size="100%">Parallel data paths in two-headed disk systems</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Software Technology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><number><style face="normal" font="default" size="100%">2</style></number><volume><style face="normal" font="default" size="100%">39</style></volume><pages><style face="normal" font="default" size="100%">125-135</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><authors><author><style face="normal" font="default" size="100%">Manolopoulos, Yannis</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%">Revell, Norman</style></author><author><style face="normal" font="default" size="100%">Tjoa, A Min</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Partial Match Retrieval in Two-Headed Disk Systems</style></title><secondary-title><style face="normal" font="default" size="100%">DEXA</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%">1995</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><volume><style face="normal" font="default" size="100%">978</style></volume><pages><style face="normal" font="default" size="100%">594-603</style></pages><isbn><style face="normal" font="default" size="100%">3-540-60303-4</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>47</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Performance of Disk Systems with Two Read/write Heads per Surface</style></title></titles><dates><year><style  face="normal" font="default" size="100%">1995</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;Our research topic is the performance of two-headed disk systems. Several scheduling algorithms have been adopted to serve read and write requests, and the expected seek has been calculated and compared to that of single-headed disk systems. Data placement schemes have been also studied in conjunction with the scheduling algorithms in order to study the efficiency and fault tolerance of two-headed disk systems. Probability theory and simulation models have been used to achieve results and reach conclusions.&lt;/p&gt;
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