Geolocation of Cultural Heritage using Multi-View Knowledge Graph Embedding

• URL: http://arxiv.org/abs/2209.03638v1
• Date: Thu, 8 Sep 2022 08:32:34 GMT
• Title: Geolocation of Cultural Heritage using Multi-View Knowledge Graph Embedding
• Authors: Hebatallah A. Mohamed, Sebastiano Vascon, Feliks Hibraj, Stuart James, Diego Pilutti, Alessio Del Bue, and Marcello Pelillo
• Abstract summary: We present a framework for ingesting knowledge about tangible cultural heritage entities. We also propose a learning model for estimating the relative distance between a pair of cultural heritage entities.
• Score: 18.822364073669583
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Knowledge Graphs (KGs) have proven to be a reliable way of structuring data. They can provide a rich source of contextual information about cultural heritage collections. However, cultural heritage KGs are far from being complete. They are often missing important attributes such as geographical location, especially for sculptures and mobile or indoor entities such as paintings. In this paper, we first present a framework for ingesting knowledge about tangible cultural heritage entities from various data sources and their connected multi-hop knowledge into a geolocalized KG. Secondly, we propose a multi-view learning model for estimating the relative distance between a given pair of cultural heritage entities, based on the geographical as well as the knowledge connections of the entities.

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