@inproceedings{yeung2007,
  author = {man Au Yeung, Ching and Gibbins, Nicholas and Shadbolt, Nigel},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  booktitle = {ESOE},
  crossref = {DBLP:conf/semweb/2007esoe},
  editor = {Chen, Liming and Cudr{\'e}-Mauroux, Philippe and Haase, Peter and Hotho, Andreas and Ong, Ernie},
  ee = {http://ceur-ws.org/Vol-292/paper11.pdf},
  interhash = {8d1bea2571673b0b9cdb818043a3a7db},
  intrahash = {38a0e7a07d8bd94b8ca7cc3cfd189b7e},
  pages = {108-121},
  publisher = {CEUR-WS.org},
  series = {CEUR Workshop Proceedings},
  title = {Understanding the Semantics of Ambiguous Tags in Folksonomies},
  volume = 292,
  year = 2007
}

@inproceedings{Kim2008,
  address = {Berlin, Deutschland},
  author = {Kim, Hak Lae and Scerri, Simon and Breslin, John G. and Decker, Stefan and Kim, Hong Gee},
  booktitle = {{Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications}},
  interhash = {9c5f5af6f47a1a563dbb405c5a58a3cc},
  intrahash = {7d3c3c2189394a8686ca9812d58bfe74},
  pages = {128--137},
  publisher = {{Dublin Core Metadata Initiative}},
  title = {{The State of the Art in Tag Ontologies: A Semantic Model for Tagging and Folksonomies}},
  year = 2008
}

@misc{Bollen2009,
  abstract = {  Most tagging systems support the user in the tag selection process by
providing tag suggestions, or recommendations, based on a popularity
measurement of tags other users provided when tagging the same resource. In
this paper we investigate the influence of tag suggestions on the emergence of
power law distributions as a result of collaborative tag behavior. Although
previous research has already shown that power laws emerge in tagging systems,
the cause of why power law distributions emerge is not understood empirically.
The majority of theories and mathematical models of tagging found in the
literature assume that the emergence of power laws in tagging systems is mainly
driven by the imitation behavior of users when observing tag suggestions
provided by the user interface of the tagging system. This imitation behavior
leads to a feedback loop in which some tags are reinforced and get more popular
which is also known as the `rich get richer' or a preferential attachment
model. We present experimental results that show that the power law
distribution forms regardless of whether or not tag suggestions are presented
to the users. Furthermore, we show that the real effect of tag suggestions is
rather subtle; the resulting power law distribution is `compressed' if tag
suggestions are given to the user, resulting in a shorter long tail and a
`compressed' top of the power law distribution. The consequences of this
experiment show that tag suggestions by themselves do not account for the
formation of power law distributions in tagging systems.
},
  author = {Bollen, Dirk and Halpin, Harry},
  interhash = {280a97ee745f4e0409cf031a1b7ea247},
  intrahash = {07fe71c72f4fe79cb5a16f53048e0abe},
  note = {cite arxiv:0903.1788
},
  title = {The Role of Tag Suggestions in Folksonomies},
  url = {http://arxiv.org/abs/0903.1788},
  year = 2009
}

@article{JamesSinclair02012008,
  abstract = {The weighted list, known popularly as a `tag cloud', has appeared on many popular folksonomy-based web-sites. Flickr, Delicious, Technorati and many   others have all featured a tag cloud at some point in their history. However, it is unclear whether the tag cloud is actually useful as an aid to finding  information. We conducted an experiment, giving participants the option of using  a tag cloud or a traditional search interface to answer various questions. We found that where the information-seeking task required specific information, participants preferred the search interface. Conversely, where the   information-seeking task was more general, participants preferred the tag cloud. While the tag cloud is not without value, it is not sufficient as the sole means  of navigation for a folksonomy-based dataset.
},
  author = {Sinclair, James and Cardew-Hall, Michael},
  doi = {10.1177/0165551506078083},
  eprint = {http://jis.sagepub.com/cgi/reprint/34/1/15.pdf},
  interhash = {9781d30a620fe81d1b6b6b06925393ab},
  intrahash = {1cc0b296c0af7c80feea7b3bb1bf825c},
  journal = {Journal of Information Science},
  number = 1,
  pages = {15-29},
  title = {{The folksonomy tag cloud: when is it useful?}},
  url = {http://jis.sagepub.com/cgi/content/abstract/34/1/15},
  volume = 34,
  year = 2008
}

@article{sinclair:ftc,
  author = {Sinclair, J. and Cardew-Hall, M.},
  interhash = {fe7fb4aad79ca5ee3ba8a5b2e1c3cd5b},
  intrahash = {539fe40eb8dd2597956cae27d6fb02ac},
  journal = {Journal of Information Science},
  pages = 016555150607808,
  publisher = {CILIP},
  title = {{The folksonomy tag cloud: When is it useful?}},
  year = 2007
}

@inproceedings{conf/www/SenVR09,
  author = {Sen, Shilad and Vig, Jesse and Riedl, John},
  booktitle = {WWW},
  crossref = {conf/www/2009},
  editor = {Quemada, Juan and León, Gonzalo and Maarek, Yoëlle S. and Nejdl, Wolfgang},
  ee = {http://doi.acm.org/10.1145/1526709.1526800},
  interhash = {4968b29a544394a5f9acd1bb8916e230},
  intrahash = {8d38bdb12f6f2f89bd3c34d200e48b72},
  isbn = {978-1-60558-487-4},
  pages = {671-680},
  publisher = {ACM},
  title = {Tagommenders: connecting users to items through tags.},
  url = {http://dblp.uni-trier.de/db/conf/www/www2009.html#SenVR09},
  year = 2009
}

@inproceedings{1180904,
  abstract = {A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.},
  address = {New York, NY, USA},
  author = {Sen, Shilad and Lam, Shyong K. and Rashid, Al Mamunur and Cosley, Dan and Frankowski, Dan and Osterhouse, Jeremy and Harper, F. Maxwell and Riedl, John},
  booktitle = {CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work},
  doi = {http://doi.acm.org/10.1145/1180875.1180904},
  interhash = {96b20bffcbc91e528461529935524b90},
  intrahash = {582641c05e7a0b9396945a951822c83f},
  isbn = {1-59593-249-6},
  location = {Banff, Alberta, Canada},
  pages = {181--190},
  publisher = {ACM},
  title = {tagging, communities, vocabulary, evolution},
  url = {http://portal.acm.org/citation.cfm?id=1180904},
  year = 2006
}

@inproceedings{mueller2013recommendations,
  abstract = {With the rising popularity of smart mobile devices, sensor data-based
 applications have become more and more popular. Their users record
 data during their daily routine or specifically for certain events.
 The application WideNoise Plus allows users to record sound samples
 and to annotate them with perceptions and tags. The app is being
 used to document and map the soundscape all over the world. The procedure
 of recording, including the assignment of tags, has to be as easy-to-use
 as possible. We therefore discuss the application of tag recommender
 algorithms in this particular scenario. We show, that this task is
 fundamentally different from the well-known tag recommendation problem
 in folksonomies as users do no longer tag fix resources but rather
 sensory data and impressions. The scenario requires efficient recommender
 algorithms that are able to run on the mobile device, since Internet
 connectivity cannot be assumed to be available. Therefore, we evaluate
 the performance of several tag recommendation algorithms and discuss
 their applicability in the mobile sensing use-case.},
  address = {Aachen, Germany},
  author = {Mueller, Juergen and Doerfel, Stephan and Becker, Martin and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Recommender Systems and the Social Web Workshop at 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China -- October 12-16, 2013. Proceedings},
  interhash = {23d1cf49208d9a0c8b883dc69d4e444d},
  intrahash = {2bab3f013052bc741e795c5c61aea5c9},
  issn = {1613-0073},
  publisher = {CEUR-WS},
  title = {Tag Recommendations for SensorFolkSonomies},
  url = {http://ceur-ws.org/Vol-1066/},
  volume = 1066,
  year = 2013
}

@inproceedings{1454017,
  address = {New York, NY, USA},
  author = {Symeonidis, Panagiotis and Nanopoulos, Alexandros and Manolopoulos, Yannis},
  booktitle = {RecSys '08: Proceedings of the 2008 ACM conference on Recommender systems},
  doi = {http://doi.acm.org/10.1145/1454008.1454017},
  interhash = {8ee38f4ffc05845fcb98f121fb265d48},
  intrahash = {e93afe409833a632af02290bbe134cba},
  isbn = {978-1-60558-093-7},
  location = {Lausanne, Switzerland},
  pages = {43--50},
  publisher = {ACM},
  title = {Tag recommendations based on tensor dimensionality reduction},
  url = {http://portal.acm.org/citation.cfm?id=1454017},
  year = 2008
}

@inproceedings{heymann2008social,
  abstract = {In this paper, we look at the "social tag prediction" problem. Given a set of objects, and a set of tags applied to those objects by users, can we predict whether a given tag could/should be applied to a particular object? We investigated this question using one of the largest crawls of the social bookmarking system del.icio.us gathered to date. For URLs in del.icio.us, we predicted tags based on page text, anchor text, surrounding hosts, and other tags applied to the URL. We found an entropy-based metric which captures the generality of a particular tag and informs an analysis of how well that tag can be predicted. We also found that tag-based association rules can produce very high-precision predictions as well as giving deeper understanding into the relationships between tags. Our results have implications for both the study of tagging systems as potential information retrieval tools, and for the design of such systems.},
  address = {New York, NY, USA},
  author = {Heymann, Paul and Ramage, Daniel and Garcia-Molina, Hector},
  booktitle = {SIGIR '08: Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval},
  doi = {http://doi.acm.org/10.1145/1390334.1390425},
  interhash = {bb9455c80cc9bd8cf95c951a1318dabc},
  intrahash = {0e6023e192f539fe4fce9894b1fbca5a},
  isbn = {978-1-60558-164-4},
  location = {Singapore, Singapore},
  pages = {531--538},
  publisher = {ACM},
  title = {Social tag prediction},
  url = {http://portal.acm.org/citation.cfm?id=1390334.1390425},
  year = 2008
}

@inproceedings{cattuto2008semantic,
  abstract = {Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For tasks like synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application.},
  author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
  booktitle = {The Semantic Web - ISWC 2008},
  doi = {10.1007/978-3-540-88564-1_39},
  interhash = {b44538648cfd476d6c94e30bc6626c86},
  intrahash = {4752f261d03cead0c52565148a0ba1c9},
  isbn = {978-3-540-88563-4},
  pages = {615--631},
  publisher = {Springer Berlin / Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {Semantic Grounding of Tag Relatedness in Social Bookmarking Systems},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/cattuto2008semantica.pdf},
  volume = 5318,
  year = 2008
}

@misc{cattuto-2008,
  abstract = { Social bookmarking systems allow users to organise collections of resources on the Web in a collaborative fashion. The increasing popularity of these systems as well as first insights into their emergent semantics have made them relevant to disciplines like knowledge extraction and ontology learning. The problem of devising methods to measure the semantic relatedness between tags and characterizing it semantically is still largely open. Here we analyze three measures of tag relatedness: tag co-occurrence, cosine similarity of co-occurrence distributions, and FolkRank, an adaptation of the PageRank algorithm to folksonomies. Each measure is computed on tags from a large-scale dataset crawled from the social bookmarking system del.icio.us. To provide a semantic grounding of our findings, a connection to WordNet (a semantic lexicon for the English language) is established by mapping tags into synonym sets of WordNet, and applying there well-known metrics of semantic similarity. Our results clearly expose different characteristics of the selected measures of relatedness, making them applicable to different subtasks of knowledge extraction such as synonym detection or discovery of concept hierarchies.},
  author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
  interhash = {cc62b733f6e0402db966d6dbf1b7711f},
  intrahash = {78fd64c3db55e6387ebdeb6c40054542},
  title = {Semantic Analysis of Tag Similarity Measures in Collaborative Tagging   Systems},
  url = {http://www.citebase.org/abstract?id=oai:arXiv.org:0805.2045},
  year = 2008
}

@inproceedings{1390423,
  address = {New York, NY, USA},
  author = {Song, Yang and Zhuang, Ziming and Li, Huajing and Zhao, Qiankun and Li, Jia and Lee, Wang-Chien and Giles, C. Lee},
  booktitle = {SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval},
  doi = {http://doi.acm.org/10.1145/1390334.1390423},
  interhash = {e6505664e875de06d98a6e787d4367d1},
  intrahash = {525a37f6ef3d81a81686b515a148b88b},
  isbn = {978-1-60558-164-4},
  location = {Singapore, Singapore},
  pages = {515--522},
  publisher = {ACM},
  title = {Real-time automatic tag recommendation},
  url = {http://portal.acm.org/citation.cfm?id=1390334.1390423},
  year = 2008
}

@incollection{m2009nliches,
  author = {Dittmann, C. and Dittmann, M. and Peters, I. and Weller, K.},
  booktitle = {Generation international - die Zukunft von Information, Wissenschaft und Profession. Proceedings der 31. Online-Tagung der Germany.},
  date = {(2009)},
  editor = {Ockenfeld, M.},
  interhash = {8b30444eb1620594515e720f6ea04def},
  intrahash = {32b5372ad9fb2c2932224454cd869afa},
  note = {Frankfurt am Main: DGI},
  pages = {117-128},
  publisher = {DGI Frankfurt a. M.},
  title = {Persönliches Tag Gardening mit tagCare.},
  url = {http://wwwalt.phil-fak.uni-duesseldorf.de/infowiss/content/mitarbeiter/peters.php},
  year = 2009
}

@inproceedings{conf/sigir/GuanBMCW09,
  author = {Guan, Ziyu and Bu, Jiajun and Mei, Qiaozhu and Chen, Chun and Wang, Can},
  booktitle = {SIGIR},
  crossref = {conf/sigir/2009},
  editor = {Allan, James and Aslam, Javed A. and Sanderson, Mark and Zhai, ChengXiang and Zobel, Justin},
  ee = {http://doi.acm.org/10.1145/1571941.1572034},
  interhash = {53d2e8bc966048bc01efcc57b2fc8250},
  intrahash = {ac9427acf51cbf7cb5a35f66a16a32c0},
  isbn = {978-1-60558-483-6},
  pages = {540-547},
  publisher = {ACM},
  title = {Personalized tag recommendation using graph-based ranking on multi-type interrelated objects.},
  url = {http://www-personal.umich.edu/~qmei/pub/sigir09-tag.pdf},
  year = 2009
}

@inproceedings{HaHe06,
  abstract = {Tagging-based systems enable users to categorize web resources by  means of tags (freely chosen keywords), in order to re-finding these  resources later. Tagging is implicitly also a social indexing process,  since users share their tags and resources, constructing a social  tag index, so-called folksonomy. At the same time of tagging-based  system, has been popularised an interface model for visual information  retrieval known as Tag-Cloud. In this model, the most frequently  used tags are displayed in alphabetical order. This paper presents  a novel approach to Tag-Cloud�s tags selection, and proposes the  use of clustering algorithms for visual layout, with the aim of improve  browsing experience. The results suggest that presented approach  reduces the semantic density of tag set, and improves the visual  consistency of Tag-Cloud layout.},
  author = {Hassan-Montero, Y. and Herrero-Solana, V.},
  booktitle = {InScit2006: International Conference on Multidisciplinary Information  Sciences and Technologies},
  file = {HaHe06.pdf:folksonomies\\HaHe06.pdf:PDF},
  interhash = {4458142370e3c6a4fe656af2f822a0dc},
  intrahash = {06f68f9fe46dc6d0f646d932e428dec9},
  misc = {comment = {proposes using k-clustering and some sort of semantic sorting  to refactor tag cloud layout to improve browsing. Not clear on how  they actually do it.}, priority = {0}, citeulike-article-id = {2045619}},
  owner = {michael},
  timestamp = {2008.01.14},
  title = {Improving Tag-Clouds as Visual Information Retrieval Interfaces},
  url = {http://nosolousabilidad.com/hassan/improving_tagclouds.pdf},
  year = 2006
}

@inproceedings{conf/wsdm/WetzkerZBA10,
  author = {Wetzker, Robert and Zimmermann, Carsten and Bauckhage, Christian and Albayrak, Sahin},
  booktitle = {WSDM},
  crossref = {conf/wsdm/2010},
  date = {2010-02-18},
  editor = {Davison, Brian D. and Suel, Torsten and Craswell, Nick and Liu, Bing},
  ee = {http://doi.acm.org/10.1145/1718487.1718497},
  interhash = {12e89c88182a393dae8d63287f65540d},
  intrahash = {54d5f72f2993a1c60d3070782bac69ac},
  isbn = {978-1-60558-889-6},
  pages = {71-80},
  publisher = {ACM},
  title = {I tag, you tag: translating tags for advanced user models.},
  url = {http://dblp.uni-trier.de/db/conf/wsdm/wsdm2010.html#WetzkerZBA10},
  year = 2010
}

@phdthesis{jschke2011formal,
  address = {[Amsterdam]},
  author = {Jäschke, Robert},
  interhash = {dcb2cd1cd72ae45d77c4d8755d199405},
  intrahash = {1ac91a922a872523de0ce8d4984e53a3},
  isbn = {9781607507079 1607507072 9783898383325 3898383326},
  pages = {--},
  publisher = {IOS Press},
  refid = {707172013},
  title = {Formal concept analysis and tag recommendations in collaborative tagging systems},
  url = {http://www.worldcat.org/search?qt=worldcat_org_all&q=9783898383325},
  year = 2011
}

@inproceedings{1458098,
  address = {New York, NY, USA},
  author = {Song, Yang and Zhang, Lu and Giles, C. Lee},
  booktitle = {CIKM '08: Proceeding of the 17th ACM conference on Information and knowledge mining},
  doi = {http://doi.acm.org/10.1145/1458082.1458098},
  interhash = {5c03bc1e658b6d44f053944418bdaec3},
  intrahash = {d330a3537b4a14fbd40661424ec8e465},
  isbn = {978-1-59593-991-3},
  location = {Napa Valley, California, USA},
  pages = {93--102},
  publisher = {ACM},
  title = {A sparse gaussian processes classification framework for fast tag suggestions},
  url = {http://portal.acm.org/citation.cfm?id=1458098},
  year = 2008
}

@inproceedings{illig2009comparison,
  abstract = {Recommendation algorithms and multi-class classifiers can support users of social bookmarking systems in assigning tags to their bookmarks. Content based recommenders are the usual approach for facing the cold start problem, i.e., when a bookmark is uploaded for the first time and no information from other users can be exploited. In this paper, we evaluate several recommendation algorithms in a cold-start scenario on a large real-world dataset. },
  address = {Berlin/Heidelberg},
  author = {Illig, Jens and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
  booktitle = {Knowledge Processing and Data Analysis},
  doi = {10.1007/978-3-642-22140-8_9},
  editor = {Wolff, Karl Erich and Palchunov, Dmitry E. and Zagoruiko, Nikolay G. and Andelfinger, Urs},
  interhash = {cd3420c0f73761453320dc528b3d1e14},
  intrahash = {f9d6e06ab0f2fdcebb77afa97d72e40a},
  isbn = {978-3-642-22139-2},
  pages = {136--149},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {A Comparison of Content-Based Tag Recommendations in Folksonomy Systems},
  url = {http://dx.doi.org/10.1007/978-3-642-22140-8_9},
  vgwort = {23},
  volume = 6581,
  year = 2011
}