@book{balbymarinho2012recommender,
  abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.},
  author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.},
  doi = {10.1007/978-1-4614-1894-8},
  interhash = {0bb7f0588cd690d67cc73e219a3a24fa},
  intrahash = {87d6883ebd98e8810be45d7e7e4ade96},
  isbn = {978-1-4614-1893-1},
  month = feb,
  publisher = {Springer},
  series = {SpringerBriefs in Electrical and Computer Engineering},
  title = {Recommender Systems for Social Tagging Systems},
  url = {http://link.springer.com/book/10.1007/978-1-4614-1894-8},
  year = 2012
}

@inproceedings{lipczak2010impact,
  abstract = {Collaborative tagging systems are popular tools for organization, sharing and retrieval of web resources. Their success is due to their freedom and simplicity of use. To post a resource, the user should only define a set of tags that would position the resource in the system's data structure -- folksonomy. This data structure can serve as a rich source of information about relations between tags and concepts they represent. To make use of information collaboratively added to folksonomies, we need to understand how users make tagging decisions. Three factors that are believed to influence user tagging decisions are: the tags used by other users, the organization of user's personal repository and the knowledge model shared between users. In our work we examine the role of another potential factor -- resource title. Despite all the advantages of tags, tagging is a tedious process. To minimize the effort, users are likely to tag with keywords that are easily available. We show that resource title, as a source of useful tags, is easy to access and comprehend. Given a choice of two tags with the same meaning, users are likely to be influenced by their presence in the title. However, a factor that seems to have stronger impact on users' tagging decisions is maintaining the consistency of the personal profile of tags. The results of our study reveal a new, less idealistic picture of collaborative tagging systems, in which the collaborative aspect seems to be less important than personal gains and convenience.},
  acmid = {1810648},
  address = {New York, NY, USA},
  author = {Lipczak, Marek and Milios, Evangelos},
  booktitle = {Proceedings of the 21st ACM Conference on Hypertext and Hypermedia},
  doi = {10.1145/1810617.1810648},
  interhash = {a999b5f2eace0cd75028e57261afe3d7},
  intrahash = {71dd1a473eaf0af9840758653746c221},
  isbn = {978-1-4503-0041-4},
  location = {Toronto, Ontario, Canada},
  numpages = {10},
  pages = {179--188},
  publisher = {ACM},
  series = {HT '10},
  title = {The Impact of Resource Title on Tags in Collaborative Tagging Systems},
  url = {http://doi.acm.org/10.1145/1810617.1810648},
  year = 2010
}

@phdthesis{jaschke2011formal,
  address = {Heidelberg},
  author = {Jäschke, Robert},
  interhash = {dcb2cd1cd72ae45d77c4d8755d199405},
  intrahash = {bad02a0bbbf066907ecdee0ecaf9fb80},
  isbn = {1-60750-707-2},
  publisher = {Akad. Verl.-Ges. AKA},
  series = {Dissertations in artificial intelligence},
  title = {Formal concept analysis and tag recommendations in collaborative tagging systems},
  url = {http://opac.bibliothek.uni-kassel.de/DB=1/PPN?PPN=231779038},
  volume = 332,
  year = 2011
}