PeRSSonal’s core functionality evaluation: Enhancing text labeling through personalized summaries

In this manuscript we present the summarization and categorization subsystems of a complete mechanism that begins with web-page fetching and concludes with representation of the collected data to the end users through a personalized portal. The system intends to collect articles from major news portals and, following an algorithmic procedure, to create a more user friendly and personalized “view” of the articles. Before presenting the information back to the end user, the core of our mechanism automatically categorizes data and then extracts personalized summaries. We focalize to the core of the mechanism and more specifically, we present the algorithms used for the summarization and the categorization of texts. The algorithms are not utilized only for producing isolated data, targeted to a specific subsystem, but a combination of the algorithms, which achieves co-operation of the categorization and summarization mechanisms, is introduced in order to enhance text labeling through the personalized summaries that are constructed.