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  • Autor
    • Kowald, Dominik
    • Lex, Elisabeth
  • TitelOvercoming the Imbalance Between Tag Recommendation Approaches and Real-World Folksonomy Structures with Cognitive-Inspired Algorithms
  • Datei
  • Persistent Identifier
  • Erschienen inarXiv.org e-Print archive
  • Erscheinungsjahr2018
  • LicenceCC-BY
  • ZugriffsrechteCC-BY
  • Download Statistik176
  • Peer ReviewJa
  • Abstract In this paper, we study the imbalance between current state-of-the-art tag recommendation algorithms and the folksonomy structures of real-world social tagging systems. While algorithms such as FolkRank are designed for dense folksonomy structures, most social tagging systems exhibit a sparse nature. To overcome this imbalance, we show that cognitive-inspired algorithms, which model the tag vocabulary of a user in a cognitive-plausible way, can be helpful. Our present approach does this via implementing the activation equation of the cognitive architecture ACT-R, which determines the usefulness of units in human memory (e.g., tags). In this sense, our long-term research goal is to design hybrid recommendation approaches, which combine the advantages of both worlds in order to adapt to the current setting (i.e., sparse vs. dense ones).