GaMuSo: Graph base music recommendation in a social bookmarking service

J. Knijf, de, A.M.L. Liekens

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


    In this work we describe a recommendation system based upon user-generated description (tags) of content. In particular, we describe an experimental system (GaMuSo) that consists of more than 140.000 user-defined tags for over 400.000 artists. From this data we constructed a bipartite graph, linking artists via tags to other artists. On the resulting graph we compute related artists for an initial artist of interest. In this work we describe and analyse our system and show that a straightforward recommendation approach leads to related concepts that are overly general, that is, concepts that are related to almost every other concept in the graph. Additionally, we describe a method to provide functional hypothesis for recommendations, given the user insight why concepts are related. GaMuSo is implemented as a webservice and available at:
    Original languageEnglish
    Title of host publicationAdvances in Intelligent Data Analysis X (10th International Symposium, IDA 2011, Porto, Portugal, October 29-31, 2011. Proceedings)
    EditorsJ. Gama, E. Bradley, J. Hollmén
    Place of PublicationBerlin
    ISBN (Print)978-3-642-24799-6
    Publication statusPublished - 2011

    Publication series

    NameLecture Notes in Computer Science
    ISSN (Print)0302-9743


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