- big spatial data processing and analytics, distributed computing, stream-based computations
- diversification in spatial query processing (return results that are diverse, as different as possible)
- furthest neighbor in very high dimensional data
- hybrid methods that combine dissimilarity, diversification and furthest neighbor searh for clustering
Georgiadis N., Tiakas E., Manolopoulos Y., Papadopoulos A.: Skyline-based dissimilarity of images. In: Journal of Intelligent Information Systems, 2019, ISSN: 1573-7675.
Georgiadis N., Tiakas E. and Manolopoulos Y.: Detecting Intrinsic Dissimilarities in Large Image Databases through Skylines, Proceedings of the 9th International Conference on Management of Emergent Digital EcoSystems (MEDES’2017), pp. 194-201, Bangkok, Thailand, 2017