@article{sun2013social,
  author = {Sun, Xiaoling and Kaur, Jasleen and Milojevic, Stasa and Flammini, Alessandro and Menczer, Filippo},
  comment = {10.1038/srep01069},
  interhash = {5cd31392e997555d78596f962044f84b},
  intrahash = {ed28353b082f3ccbd23ea85ea9d7c8e5},
  journal = {Sci. Rep.},
  month = jan,
  publisher = {Macmillan Publishers Limited. All rights reserved},
  title = {Social Dynamics of Science},
  url = {http://dx.doi.org/10.1038/srep01069},
  volume = 3,
  year = 2013
}

@article{haustein2011applying,
  abstract = {Web 2.0 technologies are finding their way into academics: specialized social bookmarking services allow researchers to store and share scientific literature online. By bookmarking and tagging articles, academic prosumers generate new information about resources, i.e. usage statistics and content description of scientific journals. Given the lack of global download statistics, the authors propose the application of social bookmarking data to journal evaluation. For a set of 45 physics journals all 13,608 bookmarks from CiteULike, Connotea and BibSonomy to documents published between 2004 and 2008 were analyzed. This article explores bookmarking data in \{STM\} and examines in how far it can be used to describe the perception of periodicals by the readership. Four basic indicators are defined, which analyze different aspects of usage: Usage Ratio, Usage Diffusion, Article Usage Intensity and Journal Usage Intensity. Tags are analyzed to describe a reader-specific view on journal content. },
  author = {Haustein, Stefanie and Siebenlist, Tobias},
  doi = {http://dx.doi.org/10.1016/j.joi.2011.04.002},
  interhash = {13fe59aae3d6ef95b529ffe00ede4126},
  intrahash = {c3e49ee7b0ed81ecd126d3ef76d5f407},
  issn = {1751-1577},
  journal = {Journal of Informetrics },
  number = 3,
  pages = {446 - 457},
  title = {Applying social bookmarking data to evaluate journal usage },
  url = {http://www.sciencedirect.com/science/article/pii/S1751157711000393},
  volume = 5,
  year = 2011
}

@article{noy2008challenge,
  abstract = {The great success of Web 2.0 is mainly fuelled by an infrastructure that allows web users to create, share, tag, and connect content and knowledge easily. The tools for developing structured knowledge in this manner have started to appear as well. However, there are few, if any, user studies that are aimed at understanding what users expect from such tools, what works and what doesn't. We organized the Collaborative Knowledge Construction (CKC) Challenge to assess the state of the art for the tools that support collaborative processes for creation of various forms of structured knowledge. The goal of the Challenge was to get users to try out different tools and to learn what users expect from such tools-features that users need, features that they like or dislike. The Challenge task was to construct structured knowledge for a portal that would provide information about research. The Challenge design contained several incentives for users to participate. Forty-nine users registered for the Challenge; thirty-three of them participated actively by using the tools. We collected extensive feedback from the users where they discussed their thoughts on all the tools that they tried. In this paper, we present the results of the Challenge, discuss the features that users expect from tools for collaborative knowledge constructions, the features on which Challenge participants disagreed, and the lessons that we learned.},
  author = {Noy, N F and Chugh, A and Alani, H},
  doi = {10.1109/MIS.2008.14},
  interhash = {df2e2abfd18d3b415d4b6a7cac970286},
  intrahash = {98dcb79390913054e6255e605223f4b2},
  journal = {IEEE Intell Syst},
  month = {1},
  number = 1,
  pages = {64-68},
  pmid = {24683367},
  title = {The CKC Challenge: Exploring Tools for Collaborative Knowledge Construction},
  url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3966208/},
  volume = 23,
  year = 2008
}

@inproceedings{heckner2009personal,
  address = {San Jose, CA, USA},
  author = {Heckner, Markus and Heilemann, Michael and Wolff, Christian},
  booktitle = {Int'l AAAI Conference on Weblogs and Social Media (ICWSM)},
  interhash = {f954e699dc6ca2d0abbe5f6ebe166dc7},
  intrahash = {d1074484ea350ad88400fe4fc6984874},
  month = may,
  title = {Personal Information Management vs. Resource Sharing: Towards a Model of Information Behaviour in Social Tagging Systems},
  year = 2009
}

@techreport{doerfel2014course,
  abstract = {Social tagging systems have established themselves as an important part in
today's web and have attracted the interest from our research community in a
variety of investigations. The overall vision of our community is that simply
through interactions with the system, i.e., through tagging and sharing of
resources, users would contribute to building useful semantic structures as
well as resource indexes using uncontrolled vocabulary not only due to the
easy-to-use mechanics. Henceforth, a variety of assumptions about social
tagging systems have emerged, yet testing them has been difficult due to the
absence of suitable data. In this work we thoroughly investigate three
available assumptions - e.g., is a tagging system really social? - by examining
live log data gathered from the real-world public social tagging system
BibSonomy. Our empirical results indicate that while some of these assumptions
hold to a certain extent, other assumptions need to be reflected and viewed in
a very critical light. Our observations have implications for the design of
future search and other algorithms to better reflect the actual user behavior.},
  author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus},
  interhash = {65f287480af20fc407f7d26677f17b72},
  intrahash = {e360f0bd207806e72305efe16491ebe3},
  note = {cite arxiv:1401.0629},
  title = {Of course we share! Testing Assumptions about Social Tagging Systems},
  url = {http://arxiv.org/abs/1401.0629},
  year = 2014
}

@inproceedings{doerfel2013analysis,
  abstract = {Since the rise of collaborative tagging systems on the web, the tag recommendation task -- suggesting suitable tags to users of such systems while they add resources to their collection -- has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.},
  acmid = {2507222},
  address = {New York, NY, USA},
  author = {Doerfel, Stephan and Jäschke, Robert},
  booktitle = {Proceedings of the 7th ACM conference on Recommender systems},
  doi = {10.1145/2507157.2507222},
  interhash = {3eaf2beb1cdad39b7c5735a82c3338dd},
  intrahash = {a73213a865503252caa4b28e88a77108},
  isbn = {978-1-4503-2409-0},
  location = {Hong Kong, China},
  numpages = {4},
  pages = {343--346},
  publisher = {ACM},
  series = {RecSys '13},
  title = {An Analysis of Tag-Recommender Evaluation Procedures},
  url = {http://doi.acm.org/10.1145/2507157.2507222},
  year = 2013
}

@inproceedings{doerfel2013analysis,
  abstract = {Since the rise of collaborative tagging systems on the web, the tag recommendation task -- suggesting suitable tags to users of such systems while they add resources to their collection -- has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.},
  acmid = {2507222},
  address = {New York, NY, USA},
  author = {Doerfel, Stephan and Jäschke, Robert},
  booktitle = {Proceedings of the 7th ACM conference on Recommender systems},
  doi = {10.1145/2507157.2507222},
  interhash = {3eaf2beb1cdad39b7c5735a82c3338dd},
  intrahash = {aa4b3d79a362d7415aaa77625b590dfa},
  isbn = {978-1-4503-2409-0},
  location = {Hong Kong, China},
  numpages = {4},
  pages = {343--346},
  publisher = {ACM},
  series = {RecSys '13},
  title = {An analysis of tag-recommender evaluation procedures},
  url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2013analysis.pdf},
  year = 2013
}

@inproceedings{doerfel2013analysis,
  abstract = {Since the rise of collaborative tagging systems on the web, the tag recommendation task -- suggesting suitable tags to users of such systems while they add resources to their collection -- has been tackled. However, the (offline) evaluation of tag recommendation algorithms usually suffers from difficulties like the sparseness of the data or the cold start problem for new resources or users. Previous studies therefore often used so-called post-cores (specific subsets of the original datasets) for their experiments. In this paper, we conduct a large-scale experiment in which we analyze different tag recommendation algorithms on different cores of three real-world datasets. We show, that a recommender's performance depends on the particular core and explore correlations between performances on different cores.},
  acmid = {2507222},
  address = {New York, NY, USA},
  author = {Doerfel, Stephan and Jäschke, Robert},
  booktitle = {Proceedings of the 7th ACM conference on Recommender systems},
  doi = {10.1145/2507157.2507222},
  interhash = {3eaf2beb1cdad39b7c5735a82c3338dd},
  intrahash = {a73213a865503252caa4b28e88a77108},
  isbn = {978-1-4503-2409-0},
  location = {Hong Kong, China},
  numpages = {4},
  pages = {343--346},
  publisher = {ACM},
  series = {RecSys '13},
  title = {An Analysis of Tag-Recommender Evaluation Procedures},
  url = {http://doi.acm.org/10.1145/2507157.2507222},
  year = 2013
}

@article{journals/insk/KrauseLHRS12,
  author = {Krause, Beate and Lerch, Hana and Hotho, Andreas and Roßnagel, Alexander and Stumme, Gerd},
  ee = {http://dx.doi.org/10.1007/s00287-010-0485-8},
  interhash = {3fca17b13ee1c002f41d3a2a4594b3e2},
  intrahash = {df97de393d3421ef2e20384ddde16ab1},
  journal = {Informatik Spektrum},
  number = 1,
  pages = {12-23},
  title = {Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy.},
  url = {http://dblp.uni-trier.de/db/journals/insk/insk35.html#KrauseLHRS12},
  volume = 35,
  year = 2012
}

@article{borrego2012measuring,
  abstract = {This paper explores the possibility of using data from social bookmarking services to measure the use of information by academic researchers. Social bookmarking data can be used to augment participative methods (e.g. interviews and surveys) and other, non-participative methods (e.g. citation analysis and transaction logs) to measure the use of scholarly information. We use BibSonomy, a free resource-sharing system, as a case study. Results show that published journal articles are by far the most popular type of source bookmarked, followed by conference proceedings and books. Commercial journal publisher platforms are the most popular type of information resource bookmarked, followed by websites, records in databases and digital repositories. Usage of open access information resources is low in comparison with toll access journals. In the case of open access repositories, there is a marked preference for the use of subject-based repositories over institutional repositories. The results are consistent with those observed in related studies based on surveys and citation analysis, confirming the possible use of bookmarking data in studies of information behaviour in academic settings. The main advantages of using social bookmarking data are that is an unobtrusive approach, it captures the reading habits of researchers who are not necessarily authors, and data are readily available. The main limitation is that a significant amount of human resources is required in cleaning and standardizing the data.},
  author = {Borrego, Ángel and Fry, Jenny},
  doi = {10.1177/0165551512438353},
  eprint = {http://jis.sagepub.com/content/38/3/297.full.pdf+html},
  interhash = {71ddfdd5b3d99b1a2986b4ded5e02b3c},
  intrahash = {e5ccbb3378eeb88e7288d8ce59539812},
  journal = {Journal of Information Science},
  number = 3,
  pages = {297--308},
  title = {Measuring researchers' use of scholarly information through social bookmarking data: A case study of BibSonomy},
  url = {http://jis.sagepub.com/content/38/3/297.abstract},
  volume = 38,
  year = 2012
}

@article{benz2010social,
  abstract = {Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind. We structure this presentation along the different interaction phases of a user with our system, coupling the relevant research questions of each phase with the corresponding implementation issues. This approach reveals in a systematic fashion important aspects and results of the broad bandwidth of folksonomy research like capturing of emergent semantics, spam detection, ranking algorithms, analogies to search engine log data, personalized tag recommendations and information extraction techniques. We conclude that when integrating a real-life application like BibSonomy into research, certain constraints have to be considered; but in general, the tight interplay between our scientific work and the running system has made BibSonomy a valuable platform for demonstrating and evaluating Web 2.0 research.},
  address = {Berlin / Heidelberg},
  affiliation = {Knowledge & Data Engineering Group, Research Center for Information Systems Design, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany},
  author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Mitzlaff, Folke and Schmitz, Christoph and Stumme, Gerd},
  doi = {10.1007/s00778-010-0208-4},
  interhash = {57fe43734b18909a24bf5bf6608d2a09},
  intrahash = {c72ed831e0d752eb3613f90e45c71c44},
  issn = {1066-8888},
  journal = {The VLDB Journal},
  keyword = {Computer Science},
  number = 6,
  pages = {849-875},
  publisher = {Springer},
  title = {The social bookmark and publication management system bibsonomy},
  url = {http://dx.doi.org/10.1007/s00778-010-0208-4},
  volume = 19,
  year = 2010
}

@inproceedings{koerner2010thinking,
  abstract = {Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence  of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise”, and (iii) in learning ontologies.},
  address = {Raleigh, NC, USA},
  author = {Körner, Christian and Benz, Dominik and Strohmaier, Markus and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proceedings of the 19th International World Wide Web Conference (WWW 2010)},
  interhash = {5afe6e4ce8357d8ac9698060fb438468},
  intrahash = {45f8d8f2a8251a5e988c596a5ebb3f2d},
  month = apr,
  publisher = {ACM},
  title = {Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity},
  url = {http://www.kde.cs.uni-kassel.de/benz/papers/2010/koerner2010thinking.pdf},
  year = 2010
}

@inproceedings{eisterlehner2010visit,
  address = {Toronto, Canada},
  author = {Mitzlaff, Folke and Benz, Dominik and Stumme, Gerd and Hotho, Andreas},
  booktitle = {Proceedings of the 21st ACM conference on Hypertext and hypermedia},
  interhash = {5584c4c57fcd8eb4663df8b114bcf09c},
  intrahash = {a97c4f7e80dcb666450acf697002155e},
  title = {Visit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy},
  year = 2010
}

@inproceedings{mitzlaff2010community,
  abstract = {Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation  of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups. This paper proposes evidence networks using implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented evidence networks using user data from the real-world social
bookmarking application BibSonomy. The results indicate that the evidence
networks reflect the relative rating of the explicit ones very well.},
  address = {Barcelona, Spain},
  author = {Mitzlaff, Folke and Atzmüller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proceedings of the Workshop on Mining Ubiquitous and Social Environments (MUSE2010)},
  interhash = {75fbc00000a1bd7ca5f93ca1d24d62c5},
  intrahash = {34d79867b23f41ca2e9f481ee894630f},
  title = {Community Assessment using Evidence Networks},
  url = {http://www.kde.cs.uni-kassel.de/ws/muse2010},
  year = 2010
}

@article{springerlink:10.1007/s00287-010-0485-8,
  abstract = {Soziale Tagging-Systeme gehören zu den in den vergangenen Jahren entstandenen Web2.0-Systemen. Sie ermöglichen es Anwendern, beliebige Informationen in das Internet einzustellen und untereinander auszutauschen. Je nach Anbieter verlinken Nutzer Videos, Fotos oder Webseiten und beschreiben die eingestellten Medien mit entsprechenden Schlagwörtern (Tags). Die damit einhergehende freiwillige Preisgabe oftmals persönlicher Informationen wirft Fragen im Bereich der informationellen Selbstbestimmung auf. Dieses Grundrecht gewährleistet dem Einzelnen, grundsätzlich selbst über die Preisgabe und Verwendung seiner persönlichen Daten zu bestimmen. Für viele Funktionalitäten, wie beispielsweise Empfehlungsdienste oder die Bereitstellung einer API, ist eine solche Kontrolle allerdings schwierig zu gestalten. Oftmals existieren keine Richtlinien, inwieweit Dienstanbieter und weitere Dritte diese öffentlichen Daten (und weitere Daten, die bei der Nutzung des Systems anfallen) nutzen dürfen. Dieser Artikel diskutiert anhand eines konkreten Systems typische, für den Datenschutz relevante Funktionalitäten und gibt Handlungsanweisungen für eine datenschutzkonforme technische Gestaltung.},
  address = {Berlin / Heidelberg},
  affiliation = {Fachgebiet Wissensverarbeitung, Universität Kassel, Kassel, Deutschland},
  author = {Krause, Beate and Lerch, Hana and Hotho, Andreas and Roßnagel, Alexander and Stumme, Gerd},
  doi = {10.1007/s00287-010-0485-8},
  interhash = {dc30e162dbb8700abdde78f86037cf2e},
  intrahash = {69f3738deecd73594907183aa874ec1a},
  issn = {0170-6012},
  journal = {Informatik-Spektrum},
  keyword = {Computer Science},
  pages = {1-12},
  publisher = {Springer},
  title = {Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy},
  url = {http://dx.doi.org/10.1007/s00287-010-0485-8},
  year = 2010
}

@article{benz2010social,
  abstract = {Social resource sharing systems are central elements of the Web 2.0 and use the same kind of lightweight knowledge representation, called folksonomy. Their large user communities and ever-growing networks of user-generated content have made them an attractive object of investigation for researchers from different disciplines like Social Network Analysis, Data Mining, Information Retrieval or Knowledge Discovery. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind. We structure this presentation along the different interaction phases of a user with our system, coupling the relevant research questions of each phase with the corresponding implementation issues. This approach reveals in a systematic fashion important aspects and results of the broad bandwidth of folksonomy research like capturing of emergent semantics, spam detection, ranking algorithms, analogies to search engine log data, personalized tag recommendations and information extraction techniques. We conclude that when integrating a real-life application like BibSonomy into research, certain constraints have to be considered; but in general, the tight interplay between our scientific work and the running system has made BibSonomy a valuable platform for demonstrating and evaluating Web 2.0 research.},
  address = {Berlin / Heidelberg},
  author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Mitzlaff, Folke and Schmitz, Christoph and Stumme, Gerd},
  doi = {10.1007/s00778-010-0208-4},
  interhash = {57fe43734b18909a24bf5bf6608d2a09},
  intrahash = {5d9541d5e8470a1867d995d3e0514697},
  issn = {1066-8888},
  journal = {The VLDB Journal},
  publisher = {Springer},
  title = {The social bookmark and publication management system BibSonomy},
  url = {http://dx.doi.org/10.1007/s00778-010-0208-4},
  year = 2010
}

@article{lerch2010datenschutz,
  author = {Lerch, Hana and Krause, Beate and Hotho, Andreas and Roßnagel, Alexander and Stumme, Gerd},
  interhash = {bbe328f35326b84db30c14648c176384},
  intrahash = {fc44b1bdc724bbda45d08e35cba8b0ec},
  journal = {MultiMedia und Recht},
  pages = {454-458},
  title = {Social Bookmarking-Systeme – die unerkannten Datensammler - Ungewollte personenbezogene Datenverabeitung?},
  volume = 7,
  year = 2010
}

@inproceedings{hotho2006bibsonomy,
  abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies and briefly describe  our own system BibSonomy, which allows for sharing both bookmarks and publication references in a kind of personal library.},
  address = {Aalborg},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures},
  editor = {de Moor, Aldo and Polovina, Simon and Delugach, Harry},
  interhash = {d28c9f535d0f24eadb9d342168836199},
  intrahash = {5854a71547051543dd3d3d5e2e2f2b67},
  isbn = {87-7307-769-0},
  pages = {87-102},
  publisher = {Aalborg Universitetsforlag},
  title = {{BibSonomy}: A Social Bookmark and Publication Sharing System},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006bibsonomy.pdf},
  year = 2006
}

@inproceedings{benz2009managing,
  abstract = {In this demo we present BibSonomy, a social bookmark and publication sharing system.},
  address = {New York, NY, USA},
  author = {Benz, Dominik and Eisterlehner, Folke and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Stumme, Gerd},
  booktitle = {HT '09: Proceedings of the 20th ACM Conference on Hypertext and Hypermedia},
  doi = {10.1145/1557914.1557969},
  editor = {Cattuto, Ciro and Ruffo, Giancarlo and Menczer, Filippo},
  interhash = {aa341801cf9a31d963fccb8a331043dc},
  intrahash = {99cafad8ce2afb5879c6c85c14cc5259},
  isbn = {978-1-60558-486-7},
  month = jun,
  pages = {323--324},
  publisher = {ACM},
  title = {Managing publications and bookmarks with BibSonomy},
  url = {http://portal.acm.org/citation.cfm?doid=1557914.1557969#},
  year = 2009
}

@inproceedings{hjss06bibsonomy,
  author = {Hotho, Andreas and J{\"a}schke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proc. of the ICCS 2006 Conceptual Structures Tool Interoperability
    Workshop},
  interhash = {5c3de78cf860c767ee40602b3a5382f3},
  intrahash = {4ca695ae4501bd56c03e435306d7c5a0},
  note = {(to appear)},
  title = {{BibSonomy}: A Social Bookmark and Publication Sharing System},
  year = 2006
}