| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Islam, Saiful
University of Bath
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2023Synthesis of Mn-Doped ZnO Nanoparticles and Their Application in the Transesterification of Castor Oil
- 2023Behavior of geomaterial composite using sugar cane bagasse ash under compressive and flexural loadingcitations
- 2022Synthesis and Experimental Investigations of Tribological and Corrosion Performance of AZ61 Magnesium Alloy Hybrid Compositescitations
- 2022Transition metal migration and O2 formation underpin voltage hysteresis in oxygen-redox disordered rocksalt cathodescitations
- 2020Deducing transport properties of mobile vacancies from perovskite solar cell characteristicscitations
- 2020Direction-based Spatial Skyline for Retrieving Arbitrary-Shaped Surrounding Objectscitations
- 2019Putting the Squeeze on Lead Iodide Perovskitescitations
- 2018Lead-Free Perovskite Semiconductors Based on Germanium-Tin Solid Solutionscitations
- 2017Structural, Electronic and Transport Properties of Hybrid SrTiO3-Graphene and Carbon Nanoribbon Interfacescitations
- 2014The Shape of TiO2-B Nanoparticlescitations
Places of action
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article
Direction-based Spatial Skyline for Retrieving Arbitrary-Shaped Surrounding Objects
Abstract
<jats:title>Abstract</jats:title><jats:p>Retrieval of arbitrary-shaped surrounding data objects has many potential applications in spatial databases including nearby arbitrary-shaped object-of-interests retrieval surrounding a user. In this paper, we propose directional zone concept to determine directional similarity among spatial data objects. Then, we propose a novel query, called direction-based spatial skyline (DSS), which retrieves non-dominated arbitrary-shaped surrounding data objects in spatial databases for a user. The proposed DSS query is rotationally invariant as well as fair. We develop efficient algorithms for processing DSS queries in spatial databases by designing novel data pruning techniques using R-Tree data indexing scheme. Finally, we demonstrate the effectiveness and efficiency of our approach by conducting extensive experiments with real datasets.</jats:p>