This repository contains a code to compute (then map) similarities between countries' place names , or toponyms. In this experiment, we collect toponyms from the Geonames dataset. To compute the similarity, toponyms are encoded in a character n-gram sequence (e.g. Paris --> {$$$P,$$Pa,$Par,Pari,...}). Character ngram are widely known to be flexible in terms if spelling errors. Here, such representation is used to capture the association between an affix and specific region. the prefix "treb" is widely seen in Bretagne (region in France) place names because it means "populated places" in the local language. Once toponyms are encoded, we produce a vector that keep counts of ngram occurrences in each country toponyms (basically a Bag-of-Words!). Finally, the cosine similarity is used to compute the similarity between these vectors.

The following map display the toponyms similarities of each country with a specific one. Here, we display similarities obtained with Mexico. In this map, you can see that Spain and South America countries' toponyms are highly similar with the ones from Mexico.

Example of map generated on Mexico

An interactive map that shows the outputs is available here

First, you need to clone the code repository using :

$ git clone https://github.com/Jacobe2169/mapthetoponymsim.git

This script was conceived in Python3.6 and requires specific libraries. Install the requirements using the following command in your terminal:

$ pip3 install -r requirements.txt

You need to download the following dataset :

• Geonames data : http://download.geonames.org/export/dump/allCountries.zip
• Countries borders shape : https://thematicmapping.org/downloads/TM_WORLD_BORDERS-0.3.zip

Then, unzip both archive in the script directory.

Use the following command:

python3 map.py

Developed by Jacques Fize