@inproceedings{hotho2006emergent,
  abstract = {Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies, briefly describeour own system BibSonomy, which allows for sharing both bookmarks andpublication references, and discuss first steps towards emergent semantics.},
  address = {Bonn},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Informatik 2006 -- Informatik für Menschen. Band 2},
  editor = {Hochberger, Christian and Liskowsky, Rüdiger},
  file = {hotho2006emergent.pdf:hotho2006emergent.pdf:PDF},
  groups = {public},
  interhash = {53e5677ab0bf1a8f5a635cc32c9082ba},
  intrahash = {05043cc20f1e0f5a612135c970e4f1ac},
  month = {October},
  note = {Proc. Workshop on Applications of Semantic Technologies, Informatik 2006},
  publisher = {Gesellschaft für Informatik},
  series = {Lecture Notes in Informatics},
  title = {Emergent Semantics in BibSonomy},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf},
  username = {dbenz},
  volume = {P-94},
  year = 2006
}

@inproceedings{aurnhammer2006augmenting,
  abstract = {We propose an approach that unifies browsing by tags and visual features for intuitive exploration of image databases. Incontrast to traditional image retrieval approaches, we utilise tags provided by users on collaborative tagging sites, complementedby simple image analysis and classification. This allows us to find new relations between data elements. We introduce theconcept of a navigation map, that describes links between users, tags, and data elements for the example of the collaborativetagging site Flickr. We show that introducing similarity search based on image features yields additional links on this map.These theoretical considerations are supported by examples provided by our system, using data and tags from real Flickr users.},
  author = {Aurnhammer, Melanie and Hanappe, Peter and Steels, Luc},
  file = {aurnhammer2006augmenting.pdf:aurnhammer2006augmenting.pdf:PDF},
  groups = {public},
  interhash = {a9d35e917da138f929b5d81f1dab4fd0},
  intrahash = {a286ce64106a503e135e7114365c77b2},
  journal = {The Semantic Web - ISWC 2006},
  pages = {58--71},
  timestamp = {2009-08-11 18:38:56},
  title = {Augmenting Navigation for Collaborative Tagging with Emergent Semantics},
  url = {http://dx.doi.org/10.1007/11926078_5},
  username = {dbenz},
  volume = 4273,
  year = 2006
}

@inproceedings{kennedy2007how,
  abstract = {The advent of media-sharing sites like Flickr and YouTube has drastically increased the volume of community-contributed multimedia resources available on the web. These collections have a previously unimagined depth and breadth, and have generated new opportunities – and new challenges – to multimedia research. How do we analyze, understand and extract patterns from these new collections? How can we use these unstructured, unrestricted community contributions of media (and annotation) to generate “knowledge�?? As a test case, we study Flickr – a popular photo sharing website. Flickr supports photo, time and location metadata, as well as a light-weight annotation model. We extract information from this dataset using two different approaches. First, we employ a location-driven approach to generate aggregate knowledge in the form of “representative tags�? for arbitrary areas in the world. Second, we use a tag-driven approach to automatically extract place and event semantics for Flickr tags, based on each tag’s metadata patterns. With the patterns we extract from tags and metadata, vision algorithms can be employed with greater precision. In particular, we demonstrate a location-tag-vision-based approach to retrieving images of geography-related landmarks and features from the Flickr dataset. The results suggest that community-contributed media and annotation can enhance and improve our access to multimedia resources – and our understanding of the world.},
  address = {New York, NY, USA},
  author = {Kennedy, Lyndon and Naaman, Mor and Ahern, Shane and Nair, Rahul and Rattenbury, Tye},
  booktitle = {MULTIMEDIA '07: Proceedings of the 15th international conference on Multimedia},
  citeulike-article-id = {2626639},
  citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1291384},
  citeulike-linkout-1 = {http://dx.doi.org/10.1145/1291233.1291384},
  doi = {10.1145/1291233.1291384},
  file = {kennedy2007how.pdf:kennedy2007how.pdf:PDF},
  groups = {public},
  interhash = {cd4acdd5a627c20e9effdbda54dd122d},
  intrahash = {7069480c43ba5d41396e075307cd1af1},
  isbn = {9781595937025},
  pages = {631--640},
  posted-at = {2009-06-25 14:41:53},
  priority = {2},
  publisher = {ACM},
  timestamp = {2011-02-17 11:07:22},
  title = {How flickr helps us make sense of the world: context and content in community-contributed media collections},
  url = {http://dx.doi.org/10.1145/1291233.1291384},
  username = {dbenz},
  year = 2007
}

@inproceedings{specia2007integrating,
  abstract = {While tags in collaborative tagging systems serve primarily an indexing purpose, facilitating search and navigation of resources, the use of the same tags by more than one individual can yield a collective classification schema. We present an approach for making explicit the semantics behind the tag space in social tagging systems, so that this collaborative organization can emerge in the form of groups of concepts and partial ontologies. This is achieved by using a combination of shallow pre-processing strategies and statistical techniques together with knowledge provided by ontologies available on the semantic web. Preliminary results on the del.icio.us and Flickr tag sets show that the approach is very promising: it generates clusters with highly related tags corresponding to concepts in ontologies and meaningful relationships among subsets of these tags can be identified.},
  author = {Specia, Lucia and Motta, Enrico},
  file = {specia2007integrating.pdf:specia2007integrating.pdf:PDF},
  groups = {public},
  interhash = {b828fbd5c9ddc4f9551f973445ecb283},
  intrahash = {8800fc1a639aeb43fd55598d2410e2e1},
  pages = {624-639},
  publisher = {Springer Berlin / Heidelberg},
  series = {Lecture Notes in Computer Science},
  timestamp = {2007-09-29 15:16:09},
  title = {Integrating Folksonomies with the Semantic Web},
  username = {dbenz},
  volume = {4519/2007},
  year = 2007
}

@inproceedings{heymann2010tagging,
  abstract = {A fundamental premise of tagging systems is that regular users can organize large collections for browsing and other tasks using uncontrolled vocabularies. Until now, that premise has remained relatively unexamined. Using library data, we test the tagging approach to organizing a collection. We find that tagging systems have three major large scale organizational features: consistency, quality, and completeness. In addition to testing these features, we present results suggesting that users produce tags similar to the topics designed by experts, that paid tagging can effectively supplement tags in a tagging system, and that information integration may be possible across tagging systems.},
  author = {Heymann, Paul and Paepcke, Andreas and Garcia-Molina, Hector},
  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/10.1145/1718487.1718495},
  file = {:heyman2010tagging.pdf:PDF},
  groups = {public},
  interhash = {d4f72ed57e6b99dbe32e18e218d81ef5},
  intrahash = {12579231cd5449f9a40cba9924975f09},
  isbn = {978-1-60558-889-6},
  pages = {51-60},
  publisher = {ACM},
  timestamp = {2010-04-08 07:27:02},
  title = {Tagging human knowledge.},
  url = {http://dblp.uni-trier.de/db/conf/wsdm/wsdm2010.html#HeymannPG10},
  username = {dbenz},
  year = 2010
}

@inproceedings{michlmayr2005case,
  abstract = {This paper delivers a case study on the properties of meta- data provided by a folksonomy. We provide the background about folk- sonomies and discuss to which extend the process of creating meta-data in a folksonomy is related to the idea of emergent semantics as defined by the IFIP 2.6 Working Group on Data Semantics. We conduct exper- iments to analyse the meta-data provided by the del.icio.us folksonomy and to develop a method for selecting subsets of meta-data that adhere to the principle of interest-based locality, which was originally observed in peer-to-peer environments. In addition, we compare data provided by del.icio.us to data provided by the DMOZ taxonomy.},
  author = {Michlmayr, Elke},
  booktitle = {Proceedings of the Workshop on Social Network Analysis, International Semantic Web Conference (ISWC)},
  file = {:michlmayr05-emergent.pdf:PDF},
  groups = {public},
  interhash = {9aa76dc961b982569554554fa3ef5de9},
  intrahash = {8799bc711fb192a577791a5fdea805f0},
  lastdatemodified = {2007-04-27},
  lastname = {Michlmayr},
  month = {November},
  own = {notown},
  pdf = {michlmayr05-emergent.pdf},
  read = {notread},
  timestamp = {2009-11-11 16:55:59},
  title = {A Case Study on Emergent Semantics in Communities},
  url = {http://wit.tuwien.ac.at/people/michlmayr/index.html},
  username = {dbenz},
  year = 2005
}

@article{golder2006structurec,
  abstract = {Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url. We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge.},
  author = {Golder, Scott and Huberman, Bernardo A.},
  file = {golder2006structure.pdf:golder2006structure.pdf:PDF},
  groups = {public},
  interhash = {03565ad9c6fc315068e528a53ed158ae},
  intrahash = {f26e96f09d59ba7d33d5339fa5d4891b},
  journal = {Journal of Information Sciences},
  journalpub = {1},
  lastdatemodified = {2007-04-27},
  lastname = {Golder},
  month = {April},
  number = 2,
  own = {own},
  pages = {198--208},
  pdf = {golder06-structure.pdf},
  read = {readnext},
  timestamp = {2011-01-28 11:35:13},
  title = {The Structure of Collaborative Tagging Systems},
  url = {http://.hpl.hp.com/research/idl/papers/tags/index.html},
  username = {dbenz},
  volume = 32,
  year = 2006
}

@inproceedings{alkhalifa2006measuring,
  abstract = {Semantic Metadata, which describes the meaning of documents, can be produced either manually or else semi-automatically using information extraction techniques. Manual techniques are expensive if they rely on skilled cataloguers, but a possible alternative is to make use of community produced annotations such as those collected in folksonomies. This paper reports on an experiment that we carried out to validate the assumption that folksonomies carry more semantic value than keywords extracted by machines. The experiment has been carried-out in two ways: automatically, by measuring the percentage of overlap between the folksonomy set and machine generated keywords set; and subjectively, by asking a human indexer to evaluate the quality of the generated keywords from both systems. The result of the experiment can be considered as evidence for the rich semantics of folksonomies, demonstrating that folksonomies used in the del.icio.us bookmarking service can be used in the process of generating semantic metadata to annotate web resources.},
  author = {Al-Khalifa, H.S. and Davis, H.C.},
  booktitle = {Innovations in Information Technology, 2006},
  file = {alkhalifa2006measuring.pdf:alkhalifa2006measuring.pdf:PDF},
  groups = {public},
  interhash = {08ff28b790e4db759b5bb5b6e5fe829a},
  intrahash = {cc23e31fcb572f0432b7f92f8b2d3663},
  month = {Nov. },
  pages = {1--5},
  timestamp = {2009-11-18 11:36:14},
  title = {Measuring the Semantic Value of Folksonomies},
  username = {dbenz},
  year = 2006
}

@article{alkhalifa2007exploring,
  abstract = {Finding good keywords to describe resources is an on-going problem: typically we select such words manually from a thesaurus of terms, or they are created using automatic keyword extraction techniques. Folksonomies are an increasingly well populated source of unstructured tags describing web resources. This paper explores the value of the folksonomy tags as potential source of keyword metadata by examining the relationship between folksonomies, community produced annotations, and keywords extracted by machines. The experiment has been carried-out in two ways: subjectively, by asking two human indexers to evaluate the quality of the generated keywords from both systems; and automatically, by measuring the percentage of overlap between the folksonomy set and machine generated keywords set. The results of this experiment show that the folksonomy tags agree more closely with the human generated keywords than those automatically generated. The results also showed that the trained indexers preferred the semantics of folksonomy tags compared to keywords extracted automatically. These results can be considered as evidence for the strong relationship of folksonomies to the human indexer’s mindset, demonstrating that folksonomies used in the del.icio.us bookmarking service are a potential source for generating semantic metadata to annotate web resources.},
  author = {Al-Khalifa, H. S. and Davis, H. C.},
  booktitle = {International Journal on Semantic Web and Information Systems(IJSWIS)},
  date = {(2007)(1)},
  file = {alkhalifa2007exploring.pdf:alkhalifa2007exploring.pdf:PDF},
  groups = {public},
  interhash = {3fbb87664648d1210a24667d8a75395a},
  intrahash = {63e591fcd456a30abf3a2e95cd11b93d},
  journal = {International Journal on Semantic Web and Information Systems (IJSWIS)},
  journalpub = {1},
  pages = {pp. 13-39},
  timestamp = {2009-11-02 18:48:05},
  title = {Exploring The Value Of Folksonomies For Creating Semantic Metadata},
  url = {http://eprints.ecs.soton.ac.uk/13555/},
  username = {dbenz},
  volume = 3,
  year = 2007
}

@inproceedings{hotho2006das,
  abstract = {Immer mehr Soziale-Lesezeichen-Systeme entstehen im heutigen Web. In solchen Systemen erstellen die Nutzer leichtgewichtige begriffliche Strukturen, so genannte Folksonomies. Ihren Erfolg verdanken sie der Tatsache, dass man keine speziellen Fähigkeiten benötigt, um an der Gestaltung mitzuwirken. In diesem Artikel beschreiben wir unser System BibSonomy. Es erlaubt das Speichern, Verwalten und Austauschen sowohl von Lesezeichen (Bookmarks) als auch von Literaturreferenzen in Form von BibTeX-Einträgen. Die Entwicklung des verwendeten Vokabulars und der damit einhergehenden Entstehung einer gemeinsamen Semantik wird detailliert diskutiert.},
  address = {Baden-Baden},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Social Software in der Wertschöpfung},
  file = {hotho2006das.pdf:hotho2006das.pdf:PDF},
  groups = {public},
  interhash = {1b39e4a77cac919f9030601711aad543},
  intrahash = {a333df6fdc7ff9322e3ce03988a7965e},
  pdf = {E:\home\help_of_all_helps.pdf},
  publisher = {Nomos},
  timestamp = {2009-09-29 12:35:44},
  title = {Das Entstehen von Semantik in BibSonomy},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006entstehen.pdf},
  username = {dbenz},
  year = 2006
}

@inproceedings{hotho2006emergent,
  abstract = {Social bookmark tools are rapidly emerging on the Web. In suchsystems users are setting up lightweight conceptual structurescalled folksonomies. The reason for their immediate success is thefact that no specific skills are needed for participating. In thispaper we specify a formal model for folksonomies, briefly describeour own system BibSonomy, which allows for sharing both bookmarks andpublication references, and discuss first steps towards emergent semantics.},
  address = {Bonn},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Informatik 2006 -- Informatik für Menschen. Band 2},
  editor = {Hochberger, Christian and Liskowsky, Rüdiger},
  file = {hotho2006emergent.pdf:hotho2006emergent.pdf:PDF},
  groups = {public},
  interhash = {53e5677ab0bf1a8f5a635cc32c9082ba},
  intrahash = {05043cc20f1e0f5a612135c970e4f1ac},
  month = {October},
  note = {Proc. Workshop on Applications of Semantic Technologies, Informatik 2006},
  publisher = {Gesellschaft für Informatik},
  series = {Lecture Notes in Informatics},
  timestamp = {2009-09-14 18:13:04},
  title = {Emergent Semantics in BibSonomy},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006emergent.pdf},
  username = {dbenz},
  volume = {P-94},
  year = 2006
}

@techreport{kome2005hierarchical,
  abstract = {The growth in digital resource repositories flickr and del.icio.us, mirrors the growth of Folksonomies to support resource classification and access. Despite this phenomenon, little is known about the effectiveness of folksonomy for retrieval and organization. Little is also known about their structure and the types of semantic relationships among folksonomy terms. This study analyzes folksonomy metadata for hierarchal semantic relationships via a content analysis of approximately 2000 folksonomy tags in over 600 individual entries. The terms were classified into groups and analyzed for hierarchical relationships. The results indicate that hierarchical relationships are part of Folksonomies. The conclusion briefly explores the potential value of thesauri for Folksonomy development, and the value of Folksonomies to thesauri developers.},
  author = {Kome, Sam H.},
  file = {kome2005hierarchical.pdf:kome2005hierarchical.pdf:PDF},
  groups = {public},
  institution = {School of Information and Library Science},
  interhash = {15b120bb7d1576ef6fd2ef63668aed6a},
  intrahash = {e59c58d6b0f6b70dd8f8d1abf3a9f9fc},
  lastdatemodified = {2006-07-17},
  lastname = {Kome},
  month = {November},
  own = {own},
  pdf = {kome05-hierarchical.pdf},
  read = {readnext},
  timestamp = {2007-09-11 13:31:29},
  title = {Hierarchical Subject Relationships in Folksonomies},
  url = {hdl.handle.net/1901/238},
  username = {dbenz},
  year = 2005
}

@inproceedings{lalwani2009deriving,
  abstract = {In this paper we describe our investigation of tagging systems and the derivation of ontological structure in the form of a folksonomy from the set of tags. Tagging systems are becoming popular, because the amount of information available on some websites is becoming too large for humans to browse manually and the types of information (multimedia data) is unsuitable for the indexers used by conventional search engines to organize. However, tag-based search is very inaccurate and incomplete (low precision and recall), because the semantics of the tags is both weak and ambiguous. The basic problem is that tags are treated like keywords by search engines, which consider individual tags in isolation. However, there is additional semantics implicit in a collection of tagged data. In this paper, we innovate and investigate techniques to make the implicit semantics explicit, so that search can be improved in both precision and recall and additional utility can be derived from the tags that people associate with multimedia items (pictures, blogs, videos, etc.). Our approach is to propose hypotheses about the ontological structure inherent in a collection of tags and then attempt to verify the hypotheses statistically. We conducted more than one hundred experimental searches on Flickr with different tags and discovered by statistical analysis information about how tags are assigned by users and what ontological knowledge is implicit in these tags that can be made explicit, and ultimately, exploited.},
  address = {New York, NY, USA},
  author = {Lalwani, Saurabh and Huhns, Michael N.},
  booktitle = {ACM-SE 47: Proceedings of the 47th Annual Southeast Regional Conference},
  doi = {http://doi.acm.org/10.1145/1566445.1566512},
  file = {lalwani2009deriving.pdf:lalwani2009deriving.pdf:PDF},
  groups = {public},
  interhash = {84ca9a71836a3475f601f6522e1d4da1},
  intrahash = {5d2c6d723aa835c4f245723200f93173},
  isbn = {978-1-60558-421-8},
  location = {Clemson, South Carolina},
  pages = {1--2},
  publisher = {ACM},
  timestamp = {2010-01-18 20:11:04},
  title = {Deriving ontological structure from a folksonomy},
  url = {http://portal.acm.org/citation.cfm?id=1566445.1566512},
  username = {dbenz},
  year = 2009
}

@inproceedings{ley2010cognitive,
  abstract = {Researching the emergence of semantics in social systems needs to take into account how users process information in their cognitive system. We report results of an experimental study in which we examined the interaction between individual expertise and the basic level advantage in collaborative tagging. The basic level advantage describes availability in memory of certain preferred levels of taxonomic abstraction when categorizing objects and has been shown to vary with level of expertise. In the study, groups of students tagged internet resources for a 10-week period. We measured the availability of tags in memory with an association test and a relevance rating and found a basic level advantage for tags from more general as opposed to specific levels of the taxonomy. An interaction with expertise also emerged. Contrary to our expectations, groups that spent less time to develop a shared understanding shifted to more specific levels as compared to groups that spent more time on a topic. We attribute this to impaired collaboration in the groups. We discuss implications for personalized tag and resource recommendations.},
  author = {Ley, Tobias and Seitlinger, Paul},
  booktitle = {CEUR Workshop Proceedings of the International Workshop on Adaptation in Social and Semantic Web (SASWeb2010)},
  editor = {Cena, Effect F. and Dattolo, A. and Kleanthous, S. and Tasso, C. and Vallejo, D. B. and Vassileva:, J.},
  file = {ley2010cognitive.pdf:ley2010cognitive.pdf:PDF},
  groups = {public},
  interhash = {dca2efa84e49e0ccb70231592df83f07},
  intrahash = {02265986290cb7b38958e7c33b2c15ad},
  pages = {13-18},
  timestamp = {2010-08-12 16:16:57},
  title = {A Cognitive Perspective on Emergent Semantics in Collaborative Tagging: The Basic Level Effect},
  url = {http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-590/sasweb10_2.pdf},
  username = {dbenz},
  volume = 590,
  year = 2010
}

@inproceedings{wu2006exploring,
  abstract = {In order to obtain a machine understandable semantics for web resources, research on the Semantic Web tries to an- notate web resources with concepts and relations from ex- plicitly de¯ned formal ontologies. This kind of formal an- notation is usually done manually or semi-automatically. In this paper, we explore a complement approach that focuses on the \social annotations of the web" which are annota- tions manually made by normal web users without a pre- de¯ned formal ontology. Compared to the formal annota- tions, although social annotations are coarse-grained, infor- mal and vague, they are also more accessible to more peo- ple and better re°ect the web resources' meaning from the users' point of views during their actual usage of the web re- sources. Using a social bookmark service as an example, we show how emergent semantics [2] can be statistically derived from the social annotations. Furthermore, we apply the de- rived emergent semantics to discover and search shared web bookmarks. The initial evaluation on our implementation shows that our method can e®ectively discover semantically related web bookmarks that current social bookmark service can not discover easily.},
  address = {New York, NY, USA},
  author = {Wu, Xian and Zhang, Lei and Yu, Yong},
  booktitle = {WWW '06: Proceedings of the 15th international conference on World Wide Web},
  file = {wu2006exploring.pdf:wu2006exploring.pdf:PDF},
  groups = {public},
  interhash = {478741551c92402f539a90a9caed61b6},
  intrahash = {2ff38a7f8e9e3941d0598877fe964eb5},
  lastdatemodified = {2007-01-04},
  lastname = {Wu},
  own = {notown},
  pages = {417--426},
  pdf = {wu06-exploring.pdf},
  publisher = {ACM Press},
  read = {notread},
  timestamp = {2007-09-11 13:31:41},
  title = {Exploring social annotations for the semantic web},
  url = {http://doi.acm.org/10.1145/1135777.1135839},
  username = {dbenz},
  year = 2006
}

@inproceedings{xu2006towards,
  abstract = {Content organization over the Internet went through several interesting phases of evolution: from structured directories to unstructured Web search engines and more recently, to tagging as a way for aggregating information, a step towards the semantic web vision. Tagging allows ranking and data organization to directly utilize inputs from end users, enabling machine processing of Web content. Since tags are created by individual users in a free form, one important problem facing tagging is to identify most appropriate tags, while eliminating noise and spam. For this purpose, we define a set of general criteria for a good tagging system. These criteria include high coverage of multiple facets to ensure good recall, least effort to reduce the cost involved in browsing, and high popularity to ensure tag quality. We propose a collaborative tag suggestion algorithm using these criteria to spot high-quality tags. The proposed algorithm employs a goodness measure for tags derived from collective user authorities to combat spam. The goodness measure is iteratively adjusted by a reward-penalty algorithm, which also incorporates other sources of tags, e.g., content-based auto-generated tags. Our experiments based on My Web 2.0 show that the algorithm is effective.},
  address = {Edinburgh, Scotland},
  author = {Xu, Zhichen and Fu, Yun and Mao, Jianchang and Su, Difu},
  booktitle = {Proceedings of the Collaborative Web Tagging Workshop at the WWW 2006},
  file = {xu2006towards.pdf:xu2006towards.pdf:PDF},
  groups = {public},
  interhash = {e18fd92b0ffa21b9f0cbb3a2fe15b873},
  intrahash = {49719d13c6da0c5f6917b97ef777184e},
  lastdatemodified = {2006-07-17},
  lastname = {Xu},
  month = May,
  own = {own},
  pdf = {xu06-towards.pdf},
  read = {readnext},
  timestamp = {2007-09-11 13:31:41},
  title = {Towards the Semantic Web: Collaborative Tag Suggestions},
  url = {http://.inf.unisi.ch/phd/mesnage/site/Readings/Readings.html},
  username = {dbenz},
  year = 2006
}

@article{zhang2006emergent,
  abstract = {Defining and using ontology to annotate web resources with semantic markups is generally perceived as the primary way to implement the vision of the Semantic Web. The ontology provides a shared and machine understandable semantics for web resources that agents and applications can utilize. This top-down approach (in the sense that an ontology is defined first on top of existing web resources and then used later to markup them), however, has a high barrier to entry and is difficult to scale up. In this paper, we investigate using a bottom-up approach for semantically annotating web resources as supported by the now widely popular social bookmarks services on the web where users can annotate and categorize web resources using �tags� freely choosen by the user without any pre-existing global semantic model. This kind of informal social categories is coined as �folksonomies�. We show how global semantics can be statistically inferred from the folksonomies to semantically annotate the web resources. The global semantic model also disambiguate the tags and group synonymous tags together. Finally, we show that there indeed are hierarchical relations among the emerged concepts in the folksonomy and it is plausible to further identify them if we use more advanced probabilistic models.},
  author = {Zhang, Lei and Wu, Xian and Yu, Yong},
  dateadded = {2007-01-04},
  file = {zhang2006emergent.pdf:zhang2006emergent.pdf:PDF},
  groups = {public},
  interhash = {bf08902c01dd395ec83cc9b7264a6099},
  intrahash = {55fd3b7ef57219ef04a9e5c904c94321},
  journal = {Journal on Data Semantics VI},
  journalpub = {1},
  lastdatemodified = {2007-01-04},
  lastname = {Zhang},
  own = {notown},
  pdf = {zhang06-emergent.pdf},
  read = {notread},
  timestamp = {2007-09-11 13:31:42},
  title = {Emergent Semantics from Folksonomies: A Quantitative Study},
  url = {http://www.springerlink.com/content/vk81621n01506652/?p=7403d6673c664a2a97131596e47ddc88&pi=7},
  username = {dbenz},
  year = 2006
}

@article{cattuto2007network,
  abstract = {Social resource sharing systems like YouTube and del.icio.us have acquired a large number of users within the last few years. They provide rich resources for data analysis, information retrieval, and knowledge discovery applications. A first step towards this end is to gain better insights into content and structure of these systems. In this paper, we will analyse the main network characteristics of two of these systems. We consider their underlying data structures - so-called folksonomies - as tri-partite hypergraphs, and adapt classical network measures like characteristic path length and clustering coefficient to them.Subsequently, we introduce a network of tag co-occurrence and investigate some of its statistical properties, focusing on correlations in node connectivity and pointing out features that reflect emergent semantics within the folksonomy. We show that simple statistical indicators unambiguously spot non-social behavior such as spam.},
  address = {Amsterdam, The Netherlands},
  author = {Cattuto, Ciro and Schmitz, Christoph and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio and Hotho, Andreas and Grahl, Miranda and Stumme, Gerd},
  file = {cattuto2007network.pdf:cattuto2007network.pdf:PDF},
  groups = {public},
  interhash = {fc5f2df61d28bc99b7e15029da125588},
  intrahash = {1dfe8b2aa29adf4929cbb845950f78bc},
  issn = {0921-7126},
  journal = {AI Communications},
  journalpub = {1},
  month = dec,
  number = 4,
  pages = {245--262},
  publisher = {IOS Press},
  timestamp = {2010-11-10 15:35:25},
  title = {Network properties of folksonomies},
  url = {http://portal.acm.org/citation.cfm?id=1365538},
  username = {dbenz},
  volume = 20,
  year = 2007
}

@inproceedings{jaeschke2007analysis,
  abstract = {BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.},
  address = {Berlin, Heidelberg},
  author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proceedings of the 15th International Conference on Conceptual Structures (ICCS 2007)},
  editor = {Priss, U. and Polovina, S. and Hill, R.},
  file = {jaeschke2007analysis.pdf:jaeschke2007analysis.pdf:PDF},
  groups = {public},
  interhash = {4352d1142afa561460511b22d4ce5103},
  intrahash = {0c2b212b9ea3d822bf4729fd5fe6b6e1},
  isbn = {3-540-73680-8},
  month = {July},
  pages = {283--295},
  publisher = {Springer-Verlag},
  series = {Lecture Notes in Artificial Intelligence},
  timestamp = {2010-11-10 15:35:25},
  title = {Analysis of the Publication Sharing Behaviour in {BibSonomy}},
  username = {dbenz},
  vgwort = {22},
  volume = 4604,
  year = 2007
}

@article{jaeschke2008discovering,
  abstract = {Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.},
  address = {New York},
  author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd},
  booktitle = {Semantic Web and Web 2.0},
  doi = {10.1016/j.websem.2007.11.004},
  editor = {Finin, T. and Mizoguchi, R. and Staab, S.},
  file = {jaeschke2008discovering.pdf:jaeschke2008discovering.pdf:PDF},
  groups = {public},
  interhash = {cfca594f9dbe30694bfbcdeb40dc4e88},
  intrahash = {18e8babe208fae2c0342438617b0ec31},
  issn = {1570-8268},
  journal = {Web Semantics: Science, Services and Agents on the World Wide Web},
  journalpub = {1},
  month = feb,
  number = 1,
  pages = {38--53},
  publisher = {Elsevier},
  timestamp = {2010-11-10 15:35:25},
  title = {Discovering Shared Conceptualizations in Folksonomies},
  url = {http://www.sciencedirect.com/science/article/B758F-4R53WD4-1/2/ae56bd6e7132074272ca2035be13781b},
  username = {dbenz},
  vgwort = {59},
  volume = 6,
  year = 2008
}