Spyros Sioutas

Spryos Sioutas obtained his diploma and Phd degree from the department of Computer Engineering and Informatics of the University of Patras. His current research interests include Spatio-Temporal Databases, Data Structures, Algorithms and I/O Complexity, Computational Geometry, Peer-to-Peer Networks, knowledge management and advanced information systems. He has published about 60 articles in international conferences, Books, Journals and Technical Reports. Main Research Interests include spatio-temporal and multimedia databases, efficient I/O algorithms and data structures, computational geometry and computer graphics, P2P computing, information systems and Web services, and educational software.

Publications

Multimedia Content's Brokerage: An Information System Based on LeSiM
Ioannis Karydis, Andreas Kanavos, Spyros Sioutas, Markos Avlonitis, Nikos Karacapilidis. © 2020. 19 pages.
Metadata-based similarity measurement is far from obsolete nowadays, despite research's focus on content and context-based information. It allows for aggregating information...
Digital Rights Management for E-Commerce Systems
Lambros Drossos, Dimitrios Tsolis, Spyros Sioutas, Theodore Papatheodorou. © 2009. 404 pages.
With the proliferation of Internet access, e-commerce systems are increasingly important as a new and effective method to distribute, transact, and exploit digital multimedia...
Indexing Techniques for Spatiotemporal Databases
George Lagogiannis, Christos Makris, Yannis Panagis, Spyros Sioutas, Evangelos Theodoridis, Athanasios Tsakalidis. © 2009. 6 pages.
We can define as spatiotemporal any database that maintains objects with geometric properties that change over time, where usual geometric properties are the spatial position and...
Web Service Integration and Management Strategies for Large-Scale Datasets
Yannis Panagis, Evangelos Sakkopoulos, Spyros Sioutas, Athanasios Tsakalidis. © 2006. 27 pages.
This chapter presents the Web Service architecture and proposes Web Service integration and management strategies for large-scale datasets. The main part of this chapter presents...