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Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Online

Code for our ArcGIS Online semantically-enriched search engine presented in our AGILE 2020 paper.

Search Engine Architecture

argis_engine

Search Engine Interface

search_engine

Search Engine Mobile Interface

mobile_start mobile_app

Python Dependencies

  • Python 3.5
  • Other required python packages are summarized in requirements.txt.

Note that if you have different version of Python3, we can simply change the python path pythonPath: '/usr/bin/python3.5' in server/routes/index.js.

NodeJS Dependencies

  • All required NodeJS packages are summarized in package.json.

To install them, do npm install.

Application

To launch this application, run npm start.

This application is sitting on top of an Elasticsearch 5.4.0 index along with a vector scoring plugin.

Word Embedding Data

You can donwload the Glove word embedding file glove.6B.100d.txt from here and put it into server/data/.

Annotation Data

AMT The Amazon Mechanical Turk data annotation interface

You can find the benchmark dataset in annotation-data/. annotation-data/f_SEM_0.html is one example suvey form for AMT annotation process.

Reference

If you find our work useful in your research please consider citing our paper.

@inproceedings{arcgisonline_agile2020,
	title={Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Online},
	author={Mai, Gengchen and Janowicz, Krzysztof and Prasad, Sathya and Shi, Meilin and Cai, Ling and Zhu, Rui and Regalia, Blake and   Lao, Ni},
	booktitle={AGILE 2020},
	year={2020},
	organization={Springer}
}