GeoWINE: Geolocation based Wiki, Image,News and Event Retrieval

TL;DR

GeoWINE is a modular system that retrieves geolocated news, images, and events from social media inputs, integrating multiple models and knowledge sources for comprehensive multimodal retrieval.

Contribution

It introduces a novel multimodal retrieval system combining geolocation estimation, entity retrieval, and news/event sources from a single image input.

Findings

Achieves promising results in entity label prediction on Google Landmarks dataset.

Provides an effective framework for geolocation-based multimedia retrieval.

Offers a publicly available demonstrator for practical use.

Abstract

In the context of social media, geolocation inference on news or events has become a very important task. In this paper, we present the GeoWINE (Geolocation-based Wiki-Image-News-Event retrieval) demonstrator, an effective modular system for multimodal retrieval which expects only a single image as input. The GeoWINE system consists of five modules in order to retrieve related information from various sources. The first module is a state-of-the-art model for geolocation estimation of images. The second module performs a geospatial-based query for entity retrieval using the Wikidata knowledge graph. The third module exploits four different image embedding representations, which are used to retrieve most similar entities compared to the input image. The embeddings are derived from the tasks of geolocation estimation, place recognition, ImageNet-based image classification, and their combination. The last two modules perform news and event retrieval from EventRegistry and the Open Event Knowledge Graph (OEKG). GeoWINE provides an intuitive interface for end-users and is insightful for experts for reconfiguration to individual setups. The GeoWINE achieves promising results in entity label prediction for images on Google Landmarks dataset. The demonstrator is publicly available at http://cleopatra.ijs.si/geowine/.