Multilabel Learning for Text-WebResource Classification

Over multiple years a large amount of web-portals developed providing their content to different groups of users. As the several content-providers usually focus on specialized fields of knowledge they developed schemes of resource-classification in terms of content-management-systems underlying the portals to manage the delivery of new published items which are often inspired by the traditional news-publishing-schemes known from the field of journalism. As users usually read across the internet over multiple sources they develop over browsing- and reading-sessions an own view which content-providers share the most relevant content such that users revisit the portals again when looking for new up-to-date content. To manage their known and read resources and for building an own library-catalogue-scheme users apply the technique of storing a web-resource shortcut-descriptor-item as bookmark to their ''bookmark-knowledge-library'' organized usually flat but partially hierarchical in bookmark folders. Over sessions it can be observed that users build their own organization and classification scheme for their shortcut-library mostly build related to the processed content.