Evaluation datasets for LuperQ

Published: 20-11-2020| Version 1 | DOI: 10.17632/g4tz8m5p6k.1
Patricia Jiménez,
Juan Carlos Roldán,
Rafael Corchuelo


This package provides everything you need to repeat the experimentation regarding the following article: A Hybrid Quantum Approach to Feed Multi-source Fusion Systems with Data from HTML tables Patricia Jiménez, Juan C. Roldán, Rafael Corchuelo Submitted to Information Fusion DATA ---- This folder provides the full repository used to perform the experimentation. It has the following sub-folders: - nishida: this folder provides the experimental tables in a format that is amenable to be used with Nishida et. al.'s proposal. - original_tables: this folder provides the experimental tables in a format that is amenable to be used with the other proposals. - tomate: this folder has some meta-data that are used for validation purposes. The annotation tool is available at http://tomatera.tdg-seville.info. There are also some additional files: - Cambria2.ttf: this is the font used in the notebook; installing it is optional. - enwiki_20180420_100d.txt: this are the embeddings computed to experiment with Nishida et. al.'s proposal. - text-metadata-dict.pk: this is a dictionary with meta-data about the tables used in the experimentation. NOTEBOOK -------- This folder provides the notebook that we prepared to perform the experimentation. Before you run it for the first time, we recommend that you should: - Create a conda environment called "luperq" in which you must install Python 3.7. - Activate the "luperq" environment. - Install the dependencies with "pip install -r requirements.txt". - Install notebook conda kernels with "conda install -n luperq nb_conda_kernels" - Install jupyter kernel with "conda install -c anaconda ipykernel" - Install jupyter kernel into the "luperq" environment with "python -m ipykernel install --user --name=luperq" To launch the experimentation environment, please, run command "launch.cmd" in Windows and "./launch.sh" in Linux. This will open the folder in Jupyter. Please, select the notebook called "Experimental-Analysis.ipynb" and follow the instructions therein. NOTES ----- LuperQ requires access to the D-Wave D-2000 Quantum Processor. Please, make your browser for https://www.dwavesys.com/ and follow the instructions therein to create your account and to install the access key required to use their processor. To facilitate testing LuperQ, this implementation uses a Simulated Annealing Sampler provided by D-Wave. Please, change it if you have a D-Wave account.


Steps to reproduce

See the README file and the article.