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WorkflowWorkflow

Music Recommendations

Recommendation engine Association rules

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This workflow takes social media data from a popular music site and uses predictive analytics to make music preference recommendations for the top artists. In addition, the workflow creates a multimedia report that shows the top artists and the other musicians associated with each in the form “Others who like X also like….”. We do this by performing an advanced association analysis and utilizing the resulting statistics to select lists of artists and recommendations. We then combine this list with overall facts about the sample and enhance the artist data with pictures to create a dynamic multi-media report. The dataset contains social networking, tagging, and music artist listening information from a set of 2K users from Last.fm online music system (http://www.last.fm).

External resources

  • Social Media Music Recommendation
  • Recommendation Engine for Retailers
  • Last.fm

Used extensions & nodes

Created with KNIME Analytics Platform version 4.1.0
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    KNIME Core Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME Itemset Mining Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.1.0

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    KNIME Reporting Runtime Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.0.0

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