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Data Models and Query Languages for Linked Geospatial Data
- Manolis Koubarakis, M. Karpathiotakis, K. Kyzirakos, Charalampos Nikolaou, Michael Sioutis
- Computer ScienceReasoning Web
- 3 September 2012
Recent advances in geospatial query processing and reasoning are surveyed, concentrating on issues of data modeling and querying.
Architecture for the heterogeneous federation of Future Internet experimentation facilities
An architecture to support a federation of Future Internet experimentation facilities, based on use cases and requirements from infrastructure owners, as well as services and first line support communities is presented.
Pushing the Envelope in Graph Compression
The analysis and experimental evaluation of the improved state-of-the-art method for the compression of web and other similar graphs shows that it outperforms the currently best method of Boldi et al. by achieving a better compression ratio and retrieval time.
Semantic Referee: A Neural-Symbolic Framework for Enhancing Geospatial Semantic Segmentation
- Marjan Alirezaie, Martin Längkvist, Michael Sioutis, A. Loutfi
- Computer ScienceSemantic Web
- 30 April 2019
A semantic referee is proposed, which is able to extract qualitative features of the errors emerging from deep machine learning frameworks and suggest corrections and how to improve the performance of semantic segmentation for satellite imagery data.
Consistency of Chordal RCC-8 Networks
- Michael Sioutis, Manolis Koubarakis
- Computer ScienceIEEE 24th International Conference on Tools with…
- 7 November 2012
Chordal RCC-8 networks are considered and it is shown that they can be checked for consistency by enforcing partial path consistency with weak composition, and that it can be solved very efficiently with PyRCC∇ by making its underlying constraint graph chordal and running path consistency on this sparse graph instead of the completion of the given network.
Efficient Approach to Solve the Minimal Labeling Problem of Temporal and Spatial Qualitative Constraints
This paper focuses on the minimal labeling problem (MLP) and proposes an algorithm to efficiently derive all the feasible base relations of a QCN and considers chordal QCNs and a new form of partial consistency which is defined as G♦-consistency.
An Efficient Approach for Tackling Large Real World Qualitative Spatial Networks
- Michael Sioutis, Jean-François Condotta, Manolis Koubarakis
- Computer ScienceInt. J. Artif. Intell. Tools
- 21 April 2016
This work proposes an implementation scheme that triangulates the constraint graphs of the input networks and uses a hash table based adjacency list to efficiently represent and reason with them and generates random scale-free-like qualitative spatial networks using the Barabasi-Albert model with a preferential attachment mechanism.
Tackling Large Qualitative Spatial Networks of Scale-Free-Like Structure
An implementation scheme that triangulates the underlying graphs of the input networks and uses a hash table based adjacency list to efficiently represent and reason with them and establishes the implementation as the only possible solution to date to reason with large scale-free-like qualitative spatial networks efficiently.
Efficient Path Consistency Algorithm for Large Qualitative Constraint Networks
For qualitative constraint networks defined over any distributive subalgebra of well-known spatio-temporal calculi, such as the Region Connection Calculus and the Interval Algebra, it is shown that DPC+ can achieve PPC very fast.
Efficiently Characterizing Non-Redundant Constraints in Large Real World Qualitative Spatial Networks
An algorithm based on ⋄G-consistency to compute the unique prime network of a RCC8 network is devised, and it significantly progresses the state-of-the-art for practical reasoning with real R CC8 networks scaling up to millions of nodes.