@inproceedings{kowald2014probability,
  abstract = {In this paper, we introduce a tag recommendation algorithm that mimics the way humans draw on items in their long-term memory. This approach uses the frequency and recency of previous tag assignments to estimate the probability of reusing a particular tag. Using three real-world folksonomies gathered from bookmarks in BibSonomy, CiteULike and Flickr, we show how incorporating a time-dependent component outperforms conventional "most popular tags" approaches and another existing and very effective but less theory-driven, time-dependent recommendation mechanism. By combining our approach with a simple resource-specific frequency analysis, our algorithm outperforms other well-established algorithms, such as FolkRank, Pairwise Interaction Tensor Factorization and Collaborative Filtering. We conclude that our approach provides an accurate and computationally efficient model of a user's temporal tagging behavior. We demonstrate how effective principles of information retrieval can be designed and implemented if human memory processes are taken into account.},
  acmid = {2576934},
  address = {Republic and Canton of Geneva, Switzerland},
  author = {Kowald, Dominik and Seitlinger, Paul and Trattner, Christoph and Ley, Tobias},
  booktitle = {Proceedings of the Companion Publication of the 23rd International Conference on World Wide Web Companion},
  doi = {10.1145/2567948.2576934},
  interhash = {911a425fa4f6e883c32fa7a09840bdd8},
  intrahash = {659fca43cb6751ee9b13297b797d91e1},
  isbn = {978-1-4503-2745-9},
  location = {Seoul, Korea},
  numpages = {6},
  pages = {463--468},
  publisher = {International World Wide Web Conferences Steering Committee},
  series = {WWW Companion '14},
  title = {Long Time No See: The Probability of Reusing Tags As a Function of Frequency and Recency},
  url = {http://dx.doi.org/10.1145/2567948.2576934},
  year = 2014
}