activity
20202026
most citedRaster Interval Object Approximations for Spatial Intersection Joins

4 citations · 7 across the 5 of their papers we have counts for

collaborators

6 papers

cs.DB2026

Pierce: GPU Ray Tracing for Spatial Joins over Complex 3D Data

Anton Hackl, Eleni Tzirita Zacharatou

Many emerging applications, from computational biology to digital twins and urban planning, rely heavily on three-dimensional spatial joins over polyhedral meshes. These joins comp…

cs.DB2023★ 2 cited

Enhancing In-Memory Spatial Indexing with Learned Search

Varun Pandey, Alexander van Renen, Eleni Tzirita Zacharatou +5

Spatial data is ubiquitous. Massive amounts of data are generated every day from a plethora of sources such as billions of GPS-enabled devices (e.g., cell phones, cars, and sensors…

cs.DB2023★ 4 cited

Raster Interval Object Approximations for Spatial Intersection Joins

Thanasis Georgiadis, Eleni Tzirita Zacharatou, Nikos Mamoulis

Spatial join processing techniques that identify intersections between complex geometries (e.g., polygons) commonly follow a two-step filter-and-refine pipeline. The filter step ev…

cs.DB2022

Satellite Image Search in AgoraEO

Ahmet Kerem Aksoy, Pavel Dushev, Eleni Tzirita Zacharatou +5

The growing operational capability of global Earth Observation (EO) creates new opportunities for data-driven approaches to understand and protect our planet. However, the current…

cs.DB2022

Efficient Specialized Spreadsheet Parsing for Data Science

Felix Henze, Haralampos Gavriilidis, Eleni Tzirita Zacharatou +1

Spreadsheets are widely used for data exploration. Since spreadsheet systems have limited capabilities, users often need to load spreadsheets to other data science environments to…

cs.DB2020★ 1 cited

The Case for Distance-Bounded Spatial Approximations

Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek +3

Spatial approximations have been traditionally used in spatial databases to accelerate the processing of complex geometric operations. However, approximations are typically only us…