%0 Journal Article
%T Clustering on Social Web
%A Tomas Kuzar
%J Information Sciences and Technologies Bulletin of the ACM Slovakia
%D 2013
%I STU Press
%X Social web increases its potential rapidly. Growing numberof involved users leads to significant increase in amountof user-generated content. End users have great opportunityto express themselves by publishing statuses, blogsor photos and in the meantime they consume the contentgenerated by others. In our work we focus on process ofsocial web data consumption - gathering, processing andvisualization. In our research we focus on processing ofunstructured textual content of Social Web in order toachieve more efficient access to relevant information. Wehave designed and evaluated methods for building precisecontent clusters by mining social web data. Our findingsindicate the need to encounter external knowledge andthe internal relationships between objects on social webto increase the accuracy of extracted knowledge. In userstudy we demonstrate how the accurate content clustersaugment the access to relevant information on the socialweb.
%K Social Web
%K Blogs
%K Content Clustering
%U http://acmbulletin.fiit.stuba.sk/vol5num1/kuzar.pdf