Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Siampou, Maria Despoina"'
The abundance of vehicle trajectory data offers a new opportunity to compute driving routes between origins and destinations. Current graph-based routing pipelines, while effective, involve substantial costs in constructing, maintaining, and updating
Externí odkaz:
http://arxiv.org/abs/2411.01325
Poly2Vec: Polymorphic Encoding of Geospatial Objects for Spatial Reasoning with Deep Neural Networks
Encoding geospatial data is crucial for enabling machine learning (ML) models to perform tasks that require spatial reasoning, such as identifying the topological relationships between two different geospatial objects. However, existing encoding meth
Externí odkaz:
http://arxiv.org/abs/2408.14806
Autor:
Hajisafi, Arash, Lin, Haowen, Shaham, Sina, Hu, Haoji, Siampou, Maria Despoina, Chiang, Yao-Yi, Shahabi, Cyrus
Forecasting the number of visits to Points-of-Interest (POI) in an urban area is critical for planning and decision-making for various application domains, from urban planning and transportation management to public health and social studies. Althoug
Externí odkaz:
http://arxiv.org/abs/2306.15927
Autor:
Papamichalopoulos, Marios, Papadakis, George, Mandilaras, George, Siampou, Maria Despoina, Mamoulis, Nikos, Koubarakis, Manolis
Geospatial data constitutes a considerable part of (Semantic) Web data, but so far, its sources are inadequately interlinked in the Linked Open Data cloud. Geospatial Interlinking aims to cover this gap by associating geometries with topological rela
Externí odkaz:
http://arxiv.org/abs/2205.01905
Autor:
Hajisafi A; Dept. of Computer Science, University of Southern California, Los Angeles, CA, USA., Siampou MD; Dept. of Computer Science, University of Southern California, Los Angeles, CA, USA., Bi J; Dept. of Computer Science, University of Southern California, Los Angeles, CA, USA., Nocera L; Dept. of Computer Science, University of Southern California, Los Angeles, CA, USA., Shahabi C; Dept. of Computer Science, University of Southern California, Los Angeles, CA, USA.
Publikováno v:
Proceedings. International Conference on Data Engineering [Proc Int Conf Data Eng] 2024 May; Vol. 2024, pp. 5425-5428. Date of Electronic Publication: 2024 Jul 23.
