mlsanityData to 14 Oct 2026

Creating Knowledge Graphs for Geographic Data on the Web

arXiv 2302.08823 ↗First posted 17 Feb 2023cs.AI cs.DB cs.IRcited by 0

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Abstract (arXiv)

Geographic data plays an essential role in various Web, Semantic Web and machine learning applications. OpenStreetMap and knowledge graphs are critical complementary sources of geographic data on the Web. However, data veracity, the lack of integration of geographic and semantic characteristics, and incomplete representations substantially limit the data utility. Verification, enrichment and semantic representation are essential for making geographic data accessible for the Semantic Web and machine learning. This article describes recent approaches we developed to tackle these challenges.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 14 references that are in the map. First posted on arXiv 17 Feb 2023.

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References · 8

  1. 2019EventKG - the Hub of Event Knowledge on the Web - and Biographical Timeline Generationcited by 24
  2. 2021GeoVectors: A Linked Open Corpus of OpenStreetMap Embeddings on World Scalecited by 12
  3. 2021WorldKG: A World-Scale Geographic Knowledge Graphcited by 11
  4. 2020Linking OpenStreetMap with Knowledge Graphs -- Link Discovery for Schema-Agnostic Volunteered Geographic Informationcited by 5
  5. 2021Towards Neural Schema Alignment for OpenStreetMap and Knowledge Graphscited by 5
  6. 2022Attention-Based Vandalism Detection in OpenStreetMapcited by 2
  7. 2021An Adaptive Clustering Approach for Accident Predictioncited by 1
  8. 2021Deep Information Fusion for Electric Vehicle Charging Station Occupancy Forecastingcited by 1

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