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This archive contains the data gathered for the following paper:

A single ZIP file can be downloaded as well.

Data

  • template/ HIT template (live version available here).
  • data/judgments.csv all the information about the HITs submitted to Mechanical Turk. Some relevant columns are:
    • Input.query ID of the query.
    • Input.docA ID of the first variation.
    • Input.docB ID of the second variation.
    • Input.time time needed to listen to all three melodies.
    • Answer.comment the comment or suggestion, if any.
    • Answer.bground the musical background, if any.
    • Answer.radio which of the variations was selected: a, b or s (they are the same).
  • data/MTurk.qrel the ground truth for all queries. The columns are the literal MTurk, the query ID, document ID and group number.

License

When using this archive, please cite the above paper:

@inproceedings{Urbano2010:crowdsourcing,
  author = {Urbano, Juli\'{a}n and Morato, Jorge and Marrero, M\'{o}nica and Mart\'{\i}n, Diego},
  booktitle = {ACM SIGIR Workshop on Crowdsourcing for Search Evaluation},
  pages = {9--16},
  title = {{Crowdsourcing Preference Judgments for Evaluation of Music Similarity Tasks}},
  year = {2010}
}

The MP3 player used in the template is redistributed from here.

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Data from the SIGIR 2010 workshop paper "Crowdsourcing Preference Judgments for Evaluation of Music Similarity Tasks"

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