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                <identifier>oai:data.mendeley.com/97m8pprdw9.1</identifier>
                <datestamp>2021-04-29T14:38:34Z</datestamp>
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    <dc:creator>Jimenez, Patricia</dc:creator>
    <dc:title>Evaluation datasets for LuperQ</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This package provides everything you need to repeat the experimentation for LuperQ.

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.&apos;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.&apos;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 &quot;luperq&quot; in which you must install Python 3.7.
- Activate the &quot;luperq&quot; environment.
- Install the dependencies with &quot;pip install -r requirements.txt&quot;.
- Install notebook conda kernels with &quot;conda install -n luperq nb_conda_kernels&quot;
- Install jupyter kernel with &quot;conda install -c anaconda ipykernel&quot;
- Install jupyter kernel into the &quot;luperq&quot; environment with &quot;python -m ipykernel install --user --name=luperq&quot;

To launch the experimentation environment, please, run command &quot;launch.cmd&quot; in Windows and &quot;./launch.sh&quot; in Linux.  This will open the folder in Jupyter.  Please, select the notebook called &quot;Experimental-Analysis.ipynb&quot; 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.</dc:description>
    <dc:subject>Applied Sciences</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/97m8pprdw9.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/97m8pprdw9.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
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    <dc:relation>https://data.mendeley.com/datasets/97m8pprdw9</dc:relation>
    <dc:date>2021-04-29T14:38:34Z</dc:date>
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