Semantic Approach for Modeling Profiles and Interactions Based on Digital Content

Abstract

A new challenge for web developers nowadays is the personalization of the social web. This means extracting data about something from different sources of information. The goal is to obtain relevant information and to create meaningful relations among data, using ontology based knowledge representation. Therefore, there is a need to talk about semantic web and certain projects that have the purpose to create communities of related entities. The solution proposed in this paper aims to generate a profile for a person, from a scientific point of view; it shows all the research a person has made, with who, and in what periods of time. It is based on a Semantic web project, the FOAF (Friend of a Friend) model. The profiles are made for a small community belonging to the Computer Science domain. The information scientific performance is extracted from different digital libraries, such as DBLP and ACM Digital Libraries. This project has a user-friendly graphical interface that allows a client, on the one hand, to insert a person's name and then to be shown the FOAF profile of the queried name, highlighting different attributes and collaborations of the person, and on the other hand, to give a list of people and to receive a list of articles they have in common. The information was extracted from the digital libraries mentioned above and we started from the premise that the data is accurate. The impact of our approach is sustained by the fact that in a small community, it is important to keep track of the research within it and the relations and collaborations between people.