@article{hotho2012publikationen,
  address = {Berlin / Heidelberg},
  affiliation = {Universität Würzburg & Forschungszentrum L3S, Würzburg, Deutschland},
  author = {Hotho, Andreas},
  doi = {10.1007/s00287-012-0653-0},
  interhash = {362bb3ae9b4d0fa01d1c8c59005ffcb7},
  intrahash = {5c84f670315f76a9e7fc9857738d571e},
  issn = {0170-6012},
  journal = {Informatik-Spektrum},
  keyword = {Computer Science},
  pages = {1-5},
  publisher = {Springer},
  title = {Publikationen im Web 2.0},
  url = {http://dx.doi.org/10.1007/s00287-012-0653-0},
  year = 2012
}

@inproceedings{krause2008logsonomy,
  abstract = {Social bookmarking systems constitute an established
part of the Web 2.0. In such systems
users describe bookmarks by keywords
called tags. The structure behind these social
systems, called folksonomies, can be viewed
as a tripartite hypergraph of user, tag and resource
nodes. This underlying network shows
specific structural properties that explain its
growth and the possibility of serendipitous
exploration.
Today’s search engines represent the gateway
to retrieve information from the World Wide
Web. Short queries typically consisting of
two to three words describe a user’s information
need. In response to the displayed
results of the search engine, users click on
the links of the result page as they expect
the answer to be of relevance.
This clickdata can be represented as a folksonomy
in which queries are descriptions of
clicked URLs. The resulting network structure,
which we will term logsonomy is very
similar to the one of folksonomies. In order
to find out about its properties, we analyze
the topological characteristics of the tripartite
hypergraph of queries, users and bookmarks
on a large snapshot of del.icio.us and
on query logs of two large search engines.
All of the three datasets show small world
properties. The tagging behavior of users,
which is explained by preferential attachment
of the tags in social bookmark systems, is
reflected in the distribution of single query
words in search engines. We can conclude
that the clicking behaviour of search engine
users based on the displayed search results
and the tagging behaviour of social bookmarking
users is driven by similar dynamics.},
  address = {New York, NY, USA},
  author = {Krause, Beate and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd},
  booktitle = {HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia},
  doi = {http://doi.acm.org/10.1145/1379092.1379123},
  interhash = {6d34ea1823d95b9dbf37d4db4d125d2a},
  intrahash = {e64d14f3207766f4afc65983fa759ffe},
  isbn = {978-1-59593-985-2},
  location = {Pittsburgh, PA, USA},
  pages = {157--166},
  publisher = {ACM},
  title = {Logsonomy - Social Information Retrieval with Logdata},
  url = {http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia},
  vgwort = {17},
  year = 2008
}

@article{jaeschke2008tag,
  abstract = {Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied.
In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of
user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences.  We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.
},
  address = {Amsterdam},
  author = {Jäschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
  doi = {10.3233/AIC-2008-0438},
  editor = {Giunchiglia, Enrico},
  interhash = {b2f1aba6829affc85d852ea93a8e39f7},
  intrahash = {955bcf14f3272ba6eaf3dadbef6c0b10},
  issn = {0921-7126},
  journal = {AI Communications},
  number = 4,
  pages = {231-247},
  publisher = {IOS Press},
  title = {Tag Recommendations in Social Bookmarking Systems},
  url = {http://dx.doi.org/10.3233/AIC-2008-0438},
  vgwort = {63},
  volume = 21,
  year = 2008
}

@article{hotho2010publikationsmanagement,
  abstract = {Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer gr{\"o}{\ss}erer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenw{\"a}rtigkeit, die st{\"a}ndige Verf{\"u}gbarkeit, aber auch die M{\"o}glichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gr{\"u}nde f{\"u}r ihren gegenw{\"a}rtigen Erfolg. Der Artikel f{\"u}hrt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabl{\"a}ufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schlie{\ss}t mit Querbez{\"u}gen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.},
  author = {Hotho, Andreas and Benz, Dominik and Eisterlehner, Folke and J{\"a}schke, Robert and Krause, Beate and Schmitz, Christoph and Stumme, Gerd},
  file = {dpunkt Product page:http\://hmd.dpunkt.de/271/05.html:URL},
  interhash = {4555775b639fe1ec65a302a61ee6532c},
  intrahash = {250d83c41fb10b89c73f54bd7040bd6e},
  issn = {1436-3011},
  journal = {HMD -- Praxis der Wirtschaftsinformatik},
  month = {#feb#},
  pages = {47-58},
  title = {{Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{\"u}r Wissenschaftler}},
  volume = {Heft 271},
  year = 2010
}

@inproceedings{krause2008antisocialb,
  author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proc. of the Fourth International Workshop on  Adversarial Information Retrieval on the Web},
  interhash = {a45d40ac7776551301ad9dde5b25357f},
  intrahash = {6357f535000a383f228f1e8e56ca86ca},
  title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems},
  url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf},
  year = 2008
}

@inproceedings{krause2008antisocialb,
  author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proc. of the Fourth International Workshop on  Adversarial Information Retrieval on the Web},
  interhash = {a45d40ac7776551301ad9dde5b25357f},
  intrahash = {6357f535000a383f228f1e8e56ca86ca},
  title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems},
  url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf},
  year = 2008
}

@article{hotho2010publikationsmanagement,
  abstract = {Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer gr{\"o}{\ss}erer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenw{\"a}rtigkeit, die st{\"a}ndige Verf{\"u}gbarkeit, aber auch die M{\"o}glichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gr{\"u}nde f{\"u}r ihren gegenw{\"a}rtigen Erfolg. Der Artikel f{\"u}hrt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabl{\"a}ufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schlie{\ss}t mit Querbez{\"u}gen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.},
  author = {Hotho, Andreas and Benz, Dominik and Eisterlehner, Folke and J{\"a}schke, Robert and Krause, Beate and Schmitz, Christoph and Stumme, Gerd},
  file = {dpunkt Product page:http\://hmd.dpunkt.de/271/05.html:URL},
  interhash = {4555775b639fe1ec65a302a61ee6532c},
  intrahash = {250d83c41fb10b89c73f54bd7040bd6e},
  issn = {1436-3011},
  journal = {HMD -- Praxis der Wirtschaftsinformatik},
  month = {#feb#},
  pages = {47-58},
  title = {{Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{\"u}r Wissenschaftler}},
  volume = {Heft 271},
  year = 2010
}

@article{hotho2010publikationsmanagement,
  abstract = {Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer gr{\"o}{\ss}erer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenw{\"a}rtigkeit, die st{\"a}ndige Verf{\"u}gbarkeit, aber auch die M{\"o}glichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gr{\"u}nde f{\"u}r ihren gegenw{\"a}rtigen Erfolg. Der Artikel f{\"u}hrt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabl{\"a}ufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schlie{\ss}t mit Querbez{\"u}gen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.},
  author = {Hotho, Andreas and Benz, Dominik and Eisterlehner, Folke and J{\"a}schke, Robert and Krause, Beate and Schmitz, Christoph and Stumme, Gerd},
  file = {dpunkt Product page:http\://hmd.dpunkt.de/271/05.html:URL},
  interhash = {4555775b639fe1ec65a302a61ee6532c},
  intrahash = {250d83c41fb10b89c73f54bd7040bd6e},
  issn = {1436-3011},
  journal = {HMD -- Praxis der Wirtschaftsinformatik},
  month = {#feb#},
  pages = {47-58},
  title = {{Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{\"u}r Wissenschaftler}},
  volume = {Heft 271},
  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
}

@inproceedings{1135863,
  abstract = {Wikipedia is the world's largest collaboratively edited source of encyclopaedic knowledge. But in spite of its utility, its contents are barely machine-interpretable. Structural knowledge, e.,g. about how concepts are interrelated, can neither be formally stated nor automatically processed. Also the wealth of numerical data is only available as plain text and thus can not be processed by its actual meaning.We provide an extension to be integrated in Wikipedia, that allows the typing of links between articles and the specification of typed data inside the articles in an easy-to-use manner.Enabling even casual users to participate in the creation of an open semantic knowledge base, Wikipedia has the chance to become a resource of semantic statements, hitherto unknown regarding size, scope, openness, and internationalisation. These semantic enhancements bring to Wikipedia benefits of today's semantic technologies: more specific ways of searching and browsing. Also, the RDF export, that gives direct access to the formalised knowledge, opens Wikipedia up to a wide range of external applications, that will be able to use it as a background knowledge base.In this paper, we present the design, implementation, and possible uses of this extension.},
  address = {New York, NY, USA},
  author = {V\"{o}lkel, Max and Kr\"{o}tzsch, Markus and Vrandecic, Denny and Haller, Heiko and Studer, Rudi},
  booktitle = {WWW '06: Proceedings of the 15th international conference on World Wide Web},
  doi = {10.1145/1135777.1135863},
  interhash = {2847e16839b842552f6f495ceda1d5d1},
  intrahash = {a204b4b6cad0255ec900ba59aec73485},
  isbn = {1-59593-323-9},
  location = {Edinburgh, Scotland},
  pages = {585--594},
  publisher = {ACM},
  title = {Semantic Wikipedia},
  url = {http://portal.acm.org/citation.cfm?id=1135863},
  year = 2006
}

@article{jaeschke2008tag,
  abstract = {Collaborative tagging systems allow users to assign keywords - so called "tags" - to resources. Tags are used for navigation, finding resources and serendipitous browsing and thus provide an immediate benefit for users. These systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In practice, however, only very basic recommendation strategies are applied.
In this paper we evaluate and compare several recommendation algorithms on large-scale real life datasets: an adaptation of
user-based collaborative filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag occurences.  We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We show, how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender.
},
  address = {Amsterdam},
  author = {Jäschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd},
  doi = {10.3233/AIC-2008-0438},
  editor = {Giunchiglia, Enrico},
  interhash = {b2f1aba6829affc85d852ea93a8e39f7},
  intrahash = {955bcf14f3272ba6eaf3dadbef6c0b10},
  issn = {0921-7126},
  journal = {AI Communications},
  number = 4,
  pages = {231-247},
  publisher = {IOS Press},
  title = {Tag Recommendations in Social Bookmarking Systems},
  url = {http://dx.doi.org/10.3233/AIC-2008-0438},
  vgwort = {63},
  volume = 21,
  year = 2008
}

@inproceedings{krause2008logsonomy,
  abstract = {Social bookmarking systems constitute an established
part of the Web 2.0. In such systems
users describe bookmarks by keywords
called tags. The structure behind these social
systems, called folksonomies, can be viewed
as a tripartite hypergraph of user, tag and resource
nodes. This underlying network shows
specific structural properties that explain its
growth and the possibility of serendipitous
exploration.
Today’s search engines represent the gateway
to retrieve information from the World Wide
Web. Short queries typically consisting of
two to three words describe a user’s information
need. In response to the displayed
results of the search engine, users click on
the links of the result page as they expect
the answer to be of relevance.
This clickdata can be represented as a folksonomy
in which queries are descriptions of
clicked URLs. The resulting network structure,
which we will term logsonomy is very
similar to the one of folksonomies. In order
to find out about its properties, we analyze
the topological characteristics of the tripartite
hypergraph of queries, users and bookmarks
on a large snapshot of del.icio.us and
on query logs of two large search engines.
All of the three datasets show small world
properties. The tagging behavior of users,
which is explained by preferential attachment
of the tags in social bookmark systems, is
reflected in the distribution of single query
words in search engines. We can conclude
that the clicking behaviour of search engine
users based on the displayed search results
and the tagging behaviour of social bookmarking
users is driven by similar dynamics.},
  address = {New York, NY, USA},
  author = {Krause, Beate and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd},
  booktitle = {HT '08: Proceedings of the Nineteenth ACM Conference on Hypertext and Hypermedia},
  doi = {http://doi.acm.org/10.1145/1379092.1379123},
  interhash = {6d34ea1823d95b9dbf37d4db4d125d2a},
  intrahash = {e64d14f3207766f4afc65983fa759ffe},
  isbn = {978-1-59593-985-2},
  location = {Pittsburgh, PA, USA},
  pages = {157--166},
  publisher = {ACM},
  title = {Logsonomy - Social Information Retrieval with Logdata},
  url = {http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Journals&title=Proceedings%20of%20the%20nineteenth%20ACM%20conference%20on%20Hypertext%20and%20hypermedia},
  vgwort = {17},
  year = 2008
}

@inproceedings{1379123,
  abstract = {Social bookmarking systems constitute an established part of the Web 2.0. In such systems users describe bookmarks by keywords called tags. The structure behind these social systems, called folksonomies, can be viewed as a tripartite hypergraph of user, tag and resource nodes. This underlying network shows specific structural properties that explain its growth and the possibility of serendipitous exploration.
Today's search engines represent the gateway to retrieve information from the World Wide Web. Short queries typically consisting of two to three words describe a user's information need. In response to the displayed results of the search engine, users click on the links of the result page as they expect the answer to be of relevance.
This clickdata can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large snapshot of del.icio.us and on query logs of two large search engines. All of the three datasets show small world properties. The tagging behavior of users, which is explained by preferential attachment of the tags in social bookmark systems, is reflected in the distribution of single query words in search engines. We can conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of social bookmarking users is driven by similar dynamics.},
  address = {New York, NY, USA},
  author = {Krause, Beate and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd},
  booktitle = {HT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia},
  doi = {http://doi.acm.org/10.1145/1379092.1379123},
  interhash = {6d34ea1823d95b9dbf37d4db4d125d2a},
  intrahash = {c7f43f2f922de1e7febedd10347e80cb},
  isbn = {978-1-59593-985-2},
  location = {Pittsburgh, PA, USA},
  pages = {157--166},
  publisher = {ACM},
  title = {Logsonomy - social information retrieval with logdata},
  url = {http://portal.acm.org/citation.cfm?id=1379092.1379123&coll=ACM&dl=ACM&type=series&idx=SERIES399&part=series&WantType=Proceedings&title=HT&CFID=825963&CFTOKEN=78379687},
  year = 2008
}

@inproceedings{cattuto08-semantic,
  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.},
  address = {Patras, Greece},
  author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proceedings of the 3rd Workshop on Ontology Learning and Population (OLP3)},
  interhash = {cc62b733f6e0402db966d6dbf1b7711f},
  intrahash = {3b0aca61b24e4343bd80390614e3066e},
  month = {July},
  title = {Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems},
  url = {http://olp.dfki.de/olp3/},
  year = 2008
}

@inproceedings{krause2008antisocial,
  author = {Krause, Beate and Schmitz, Christoph and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proc. of the Fourth International Workshop on  Adversarial Information Retrieval on the Web},
  interhash = {a45d40ac7776551301ad9dde5b25357f},
  intrahash = {6357f535000a383f228f1e8e56ca86ca},
  title = {The Anti-Social Tagger - Detecting Spam in Social Bookmarking Systems},
  url = {http://airweb.cse.lehigh.edu/2008/submissions/krause_2008_anti_social_tagger.pdf},
  year = 2008
}

@article{BenjaminsDaviesEtAl08intelligent,
  abstract = {The Semantic Web has recently been enjoying significant investment
	in research, start-ups, and commercial projects. In this installment
	of Trends and Controversies, several experts discuss what they hope
	semantic technology will accomplish in the near future.},
  author = {Benjamins, V. Richard and Davies, John and Baeza-Yates, Ricardo and Mika, Peter and Zaragoza, Hugo and Greaves, Mark and Gomez-Perez, Jose Manuel and Contreras, Jesus and Domingue, John and Fensel, Dieter},
  doi = {10.1109/MIS.2008.10},
  file = {IEEE Digital Library:2008/BenjaminsDaviesEtAl08intelligent.pdf:PDF},
  interhash = {20453904199d02c9a2504e356723b920},
  intrahash = {b676addcf02f7cb15d9069aed1d0d0fd},
  issn = {1541-1672},
  journal = {Intelligent Systems},
  number = 1,
  owner = {flint},
  pages = {76-88},
  timestamp = {2008.02.04},
  title = {Near-Term Prospects for Semantic Technologies},
  volume = 23,
  year = 2008
}

@article{michael2006social,
  abstract = {Zusammenfassung  Ausgehend vom Begriff des Web 2.0 werden die Merkmale und Möglichkeiten sog. Social Software vorgestellt. Der Beitrag erläutert
den Begriff und gibt einen Überblick über die unterschiedlichen Arten. Merkmale und Nutzenpotentiale sowie Beispiele werdenvorgestellt.},
  author = {Bächle, Michael},
  interhash = {9c13392522490174c44b2562d13193f7},
  intrahash = {9f3afc8a39415b9a6a58c8c8c570f1d5},
  journal = {Informatik-Spektrum},
  month = {#apr#},
  number = 2,
  pages = {121--124},
  title = {Social Software},
  url = {http://dx.doi.org/10.1007/s00287-006-0063-2},
  volume = 29,
  year = 2006
}

@book{3486585797,
  asin = {3486585797},
  ean = {9783486585797},
  editor = {Back, Andrea and Gronau, Norbert and Tochtermann, Klaus},
  interhash = {ea1de09c52cb4e5d9bf02e3b3ac3e368},
  intrahash = {8d0be8fb962353f9cb5615c35e0ccdb1},
  isbn = {3486585797},
  publisher = {Oldenbourg},
  title = {Web 2.0 in der Unternehmenspraxis: Grundlagen, Fallstudien und Trends zum Einsatz von Social Software},
  url = {http://www.amazon.de/Web-2-0-Unternehmenspraxis-Grundlagen-Fallstudien/dp/3486585797%3FSubscriptionId%3D13CT5CVB80YFWJEPWS02%26tag%3Dws%26linkCode%3Dxm2%26camp%3D2025%26creative%3D165953%26creativeASIN%3D3486585797},
  year = 2008
}

@article{mcafee2006enterprise,
  author = {McAfee, Andrew P.},
  interhash = {99d85d826884aaff74f80153be45c40e},
  intrahash = {d1be3618b49f77d9e2d40310d5b9c18a},
  journal = {MITSloan Management Review},
  number = 3,
  pages = {21-28},
  title = {Enterprise 2.0: The Dawn of Emergent Collaboration},
  url = {http://sloanreview.mit.edu/the-magazine/articles/2006/spring/47306/enterprise-the-dawn-of-emergent-collaboration/},
  volume = 47,
  year = 2006
}

@mastersthesis{eprints315620,
  abstract = {Web 2.0, the social, interactive and user-oriented web, is an integral component of current web applications. In the context of Library 2.0-motivated service developments, some libraries already have implemented such features in their local online library catalogues. However, many library associations and library service centres that provide union catalogues seem to be reluctant to keep pace with these developments. This thesis gives an overview of existing union catalogues in the German-speaking language area that already use Web 2.0 features. Furthermore, it identifies opportunities and risks when implementing Web 2.0 concepts in a union catalogue based on a market-analysis and in-depth interviews with experts for library systems and union catalogues. The empirical study of this thesis also contains an evaluation of the existing union catalogue of the umbrella organisation of public libraries in Austria, called ?B?chereiverband ?sterreichs? (BV?). The result of this thesis includes that providers of union catalogues are aware of the relevance of the new technologies as additional features to improve the usability of union catalogues and to enrich bibliographic data with supplementary content. Still, the implementation of web 2.0 services seems to be hesitant within the German-speaking countries. The main task of union catalogues is still to provide easy and fast access to bibliographic data but web 2.0 concepts will be an important add-on in the future.},
  author = {Haubenwaller, Barbara},
  interhash = {7e2ada4fce0c64829c8446d4f0ee9194},
  intrahash = {e4e3604c5ebbf237222143e5ba94ae86},
  month = {January},
  school = {University of Applied Sciences Campus02 Fachhochschule der Wirtschaft Graz (Austria)},
  title = {HERAUSFORDERUNG BIBLIOTHEK 2.0: Chancen und Risiken für Verbundkataloge durch die Anreicherung mit Web 2.0-Konzepten },
  url = {http://eprints.rclis.org/15620/},
  year = 2009
}

@book{berendt09knowledge,
  address = {Heidelberg},
  author = {?},
  interhash = {12fa8ec01220bd1e437a945ea1972a09},
  intrahash = {d3aee79927e4d00aa1408d2a26749778},
  note = {(to appear)},
  publisher = {Springer},
  title = {Knowledge Discovery Enhanced with Semantic and Social Information},
  year = {2009 }
}

@book{berendt2008challenge,
  editor = {Berendt, Bettina and Glance, Natalie and Hotho, Andreas},
  interhash = {ab9a3d6f27b2bc93cb8137a0f7988271},
  intrahash = {50f6cd75018d7ee98f49c5ab4ef0faaf},
  publisher = {Workshop at 18th Europ. Conf. on Machine Learning (ECML'08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'08)},
  title = {Wikis, Blogs, Bookmarking Tools - Mining the Web 2.0 Workshop},
  url = {http://www.kde.cs.uni-kassel.de/ws/wbbtmine2008/pdf/all_wbbtmine2008.pdf},
  year = 2008
}

@inproceedings{AlKhalifa:2007,
  abstract = {Users tag resources for a variety of reasons and using a variety of conventions. The tags that they provide are stored in social bookmarking services, so these services can provide a rich gateway to a wide and interesting quantity of web resources. The cognitive effort that has gone into making these tags has presumably added value to the description of the resource. In this work we utilize the quantitative value of these tags for ranking bookmarked web resources in social bookmarking services. Our proposed solution is called CoolRank, a simple and intuitive model to rank bookmarked web resources in a social bookmarking service, such as del.icio.us. CoolRank makes use of both quantitative information, based on the number of people who have bookmarked a web resource, and subjective information, based on the words people have used in their tags.},
  author = {Al-Khalifa, H.S.},
  booktitle = {Innovations in Information Technology, 2007. Innovations '07. 4th International Conference on},
  doi = {10.1109/IIT.2007.4430482},
  interhash = {a6babb1a2f926cca3e8fe0258337e864},
  intrahash = {4671fb1c606e3d7f559bb25d9b20e47d},
  isbn = {978-1-4244-1841-1},
  pages = {208-212},
  title = {CoolRank: A Social Solution for Ranking Bookmarked Web Resources},
  url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4430482},
  year = 2007
}

@article{1276056,
  address = {Amsterdam, The Netherlands, The Netherlands},
  author = {Wurst, Michael and Morik, Katharina},
  doi = {http://dx.doi.org/10.1016/j.future.2006.04.004},
  interhash = {591e4b107d4a5cafc0cf49e07fad72e0},
  intrahash = {e5eba80e58b4532a3fd3bcf50994734e},
  issn = {0167-739X},
  journal = {Future Gener. Comput. Syst.},
  number = 1,
  pages = {69--75},
  publisher = {Elsevier Science Publishers B. V.},
  title = {Distributed feature extraction in a p2p setting: a case study},
  url = {http://portal.acm.org/citation.cfm?id=1276056},
  volume = 23,
  year = 2007
}

@misc{cattuto-2007,
  author = {Cattuto, Ciro and Baldassarri, Andrea and Servedio, Vito D. P. and Loreto, Vittorio},
  interhash = {7de017393b2d48335e209a9db23e08b6},
  intrahash = {4d6bfbd16ba976f4a4aae985c2a92449},
  title = {Vocabulary growth in collaborative tagging systems},
  url = {http://www.citebase.org/abstract?id=oai:arXiv.org:0704.3316},
  year = 2007
}

@article{danowski2006bzb,
  author = {DANOWSKI, Patrick and HELLER, Lambert},
  interhash = {5cb584495b0607f3223eff5b211d6354},
  intrahash = {b2f1e3b766f66f01997a086ac024f8dd},
  journal = {Bibliotheksdienst},
  number = 11,
  pages = {1259--1271},
  publisher = {Deutsches Bibliotheksinstitut},
  title = {{Bibliothek 2. 0: Die Zukunft der Bibliothek?}},
  url = {http://www.zlb.de/aktivitaeten/bd_neu/heftinhalte2006/DigitaleBib011106.pdf},
  volume = 40,
  year = 2006
}

@inproceedings{marlow2006position,
  abstract = {In recent years, tagging systems have become increasingly popular. These systems enable users to add keywords (i.e., “tags”) to Internet resources (e.g., web pages, images, videos) without relying on a controlled vocabulary. Tagging systems have the potential to improve search, spam detection, reputation systems, and personal organization while introducing new modalities of social communication and opportunities for data mining. This potential is largely due to the social structure that underlies many of the current systems. Despite the rapid expansion of applications that support tagging of resources, tagging systems are still not well studied or understood. In this paper, we provide a short description of the academic related work to date. We offer a model of tagging systems, specifically in the context of web-based systems, to help us illustrate the possible benefits of these tools. Since many such systems already exist, we provide a taxonomy of tagging systems to help inform their analysis and design, and thus enable researchers to frame and compare evidence for the sustainability of such systems. We also provide a simple taxonomy of incentives and contribution models to inform potential evaluative frameworks. While this work does not present comprehensive empirical results, we present a preliminary study of the photosharing and tagging system Flickr to demonstrate our model and explore some of the issues in one sample system. This analysis helps us outline and motivate possible future directions of research in tagging systems.},
  author = {Marlow, Cameron and Naaman, Mor and Boyd, Danah and Davis, Marc},
  booktitle = {Collaborative Web Tagging Workshop at WWW2006},
  interhash = {7446351e0d902ee4f36fb750f82c50a5},
  intrahash = {8b100f88154692615b1e31e2e243e78c},
  location = {Edinburgh, Scotland},
  month = May,
  title = {{Position Paper, Tagging, Taxonomy, Flickr, Article, ToRead}},
  url = {http://www.danah.org/papers/WWW2006.pdf},
  year = 2006
}

@inproceedings{Mika2005,
  author = {Mika, Peter},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  booktitle = {International Semantic Web Conference},
  doi = {10.1007/11574620_38},
  ee = {http://dx.doi.org/10.1007/11574620_38},
  interhash = {5ea12110b5bb0e3a8ad09aeb16a70cdb},
  intrahash = {6929599cc8fbdc408282907eeec37204},
  owner = {mlux},
  pages = {522-536},
  publisher = {Springer},
  series = {LNCS},
  timestamp = {2006.01.19},
  title = {Ontologies Are Us: A Unified Model of Social Networks and Semantics},
  url = {http://www.cs.vu.nl/~pmika/research/papers/ISWC-folksonomy.pdf},
  year = 2005
}

@article{web06Alby,
  asin = {3446409319},
  author = {Alby, Tom},
  interhash = {191c23c1a0c518a256dbde1c0feae0c5},
  intrahash = {ad1e12ff8ce3f6f1f7f97bd29236060b},
  publisher = {Hanser Fachbuchverlag},
  title = {Web 2.0. Konzepte, Anwendungen, Technologien},
  typesource = {Simple CitationSource},
  url = {http://www.amazon.de/exec/obidos/ASIN/3446409319/daswesendigitale/},
  year = 2006
}

@inproceedings{citeulike:771813,
  abstract = {We describe a technology exploration of social bookmarking within a closed, corporate environment. We hypothesize that such a tool would be valuable for information sharing, information management, and social networking in our organization. In order to assess the value of social software, we have embarked upon a 6-month pilot, or trial period, where we are striving to reach critical mass through marketing strategies and targeting influential figures with large, social networks. Our goal is to demonstrate the utility of social bookmarking within our corporation and to explore some of the social influences and behavioral evolution.},
  author = {Damianos, Laurie and Griffith, John and Cuomo, Donna and Hirst, David and Smallwood, James},
  booktitle = {Collaborative Web Tagging Workshop at WWW2006, Edinburgh, Scotland},
  citeulike-article-id = {771813},
  interhash = {17fc98ebe0777644a3439204fdeab745},
  intrahash = {4f7acbf38a2dcaaa411979a0994da26c},
  month = May,
  priority = {2},
  title = {Onomi: Social Bookmarking on a Corporate Intranet},
  url = {http://www.rawsugar.com/www2006/28.pdf},
  year = 2006
}

@article{Ha05,
  author = {Hammond, Tony and Hannay, Timo and Lund, Ben and Scott, Joanna},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  interhash = {c7457d9dc07545a061de119d96ca4e47},
  intrahash = {89c6c43ad692ccfbe4c09d31926ab8a7},
  isbn = {3-540-60161-9},
  journal = {D-Lib Magazine},
  month = {April},
  number = 4,
  organization = {{N}ature {P}ublishing {G}roup},
  title = {{S}ocial {B}ookmarking {T}ools ({I}): {A} {G}eneral {R}eview},
  url = {http://www.dlib.org/dlib/april05/hammond/04hammond.html},
  volume = 11,
  year = 2005
}