Today there is an abundance of data on line. The grand challenge is turning this huge amount of data to knowledge useful to the individual users of the Internet. DiP3 will address this challenge by tackling one form of data processing, often referred to as “push” data delivery. In push data delivery, instead of explicitly searching for information, users get notified when relevant information becomes available. Examples of such systems include RSS feeds, news alerts and aggregators. The scientific objective of the proposal is to derive models, algorithms and techniques to control both the amount and quality of information received by users. To this end, we propose incorporating user preferences in data delivery to rank data items based on their relevance to the users. Although preference specification has been extensively studied, there is little previous research work on incorporating preferences in Internet-scale data delivery. Furthermore, DIP3 will exploit the inherent social connections between users in Web 2.0 as expressed through social networks, social tagging, and other community-based features to enhance preference specification and ranked information delivery. The project will focus on two issues central to the success of such systems: privacy preservation and performance. Besides the sought research achievements, the main objective of the project is to reinforce the international dimension of the career of the European researcher by giving her the opportunity to be trained at the outgoing host institution, namely the College of Computing in Georgia Institute of Technology, US, whose graduate program is listed among the top-10 ones in the US for 2008. Within the College, the DiSL lab produces high-level research in large-scale distributed systems examining performance, security and privacy. The researcher will return to her institution, the Computer Science Department of the University of Ioannina, with new knowledge and experience.
Fields of science
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