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Towards Leveraging Link Prediction for Geospatial Data Integration
Conference proceeding   Open access   Peer reviewed

Towards Leveraging Link Prediction for Geospatial Data Integration

Proceedings of the 33rd. Italian Symposium on Database Systems (SEBD 2025), Vol.4182, pp.95-104
CEUR Workshop Proceedings, 4182
Italian Symposium on Database Systems (SEBD) (Ischia, 16/06/2025–19/06/2025)
2025
Handle:
https://hdl.handle.net/10863/52421

Abstract

Geospatial data Knowledge completion Knowledge Graphs Knowledge integration Link prediction
Link prediction is a technique used to predict new relationships between entities in a given graph. There are several domains in which this technique is applied. Those span from social media friendship links suggestions to correlated products prediction. Nevertheless, the use of link prediction to support knowledge integration is still a subject of debate, especially in the context of geospatial data. In this paper, we aim to discuss the role and some of the potential benefits of link prediction in the context of geospatial data completion and integration. To this end, we aim to position and discuss the role of geospatial link prediction within the framework of Ontology-Based Data Access (OBDA), highlighting the potential contribution of link prediction in this field. Additionally, we present a series of preliminary experiments designed to predict relationships of “competition” among business activities within a specific geographic area. Finally, we explore how the injection of knowledge from information-rich schemas about concepts related to the geospatial domain can positively influence the accuracy of the prediction model.
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