@book{balbymarinho2012recommender, abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.}, added-at = {2012-02-14T08:29:50.000+0100}, author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.}, biburl = {http://www.bibsonomy.org/bibtex/287d6883ebd98e8810be45d7e7e4ade96/hotho}, interhash = {0bb7f0588cd690d67cc73e219a3a24fa}, intrahash = {87d6883ebd98e8810be45d7e7e4ade96}, isbn = {978-1-4614-1893-1}, keywords = {tagging social recommender myown folksonomy collaborative bookmarking 2012}, month = feb, publisher = {Springer}, series = {SpringerBriefs in Electrical and Computer Engineering}, title = {Recommender Systems for Social Tagging Systems}, url = {http://www.springer.com/computer/database+management+%26+information+retrieval/book/978-1-4614-1893-1}, year = 2012 } @book{balbymarinho2012recommender, abstract = {Social Tagging Systems are web applications in which users upload resources (e.g., bookmarks, videos, photos, etc.) and annotate it with a list of freely chosen keywords called tags. This is a grassroots approach to organize a site and help users to find the resources they are interested in. Social tagging systems are open and inherently social; features that have been proven to encourage participation. However, with the large popularity of these systems and the increasing amount of user-contributed content, information overload rapidly becomes an issue. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In social tagging systems, however, we face new challenges. While in classic recommender systems the mode of recommendation is basically the resource, in social tagging systems there are three possible modes of recommendation: users, resources, or tags. Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this book, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve social tagging systems. The book is divided into self-contained chapters covering the background material on social tagging systems and recommender systems to the more advanced techniques like the ones based on tensor factorization and graph-based models.}, added-at = {2012-02-13T12:52:23.000+0100}, author = {Balby Marinho, L. and Hotho, A. and Jäschke, R. and Nanopoulos, A. and Rendle, S. and Schmidt-Thieme, L. and Stumme, G. and Symeonidis, P.}, biburl = {http://www.bibsonomy.org/bibtex/287d6883ebd98e8810be45d7e7e4ade96/jaeschke}, interhash = {0bb7f0588cd690d67cc73e219a3a24fa}, intrahash = {87d6883ebd98e8810be45d7e7e4ade96}, isbn = {978-1-4614-1893-1}, keywords = {tagging social recommender myown folksonomy collaborative bookmarking 2012}, month = feb, publisher = {Springer}, series = {SpringerBriefs in Electrical and Computer Engineering}, title = {Recommender Systems for Social Tagging Systems}, url = {http://www.springer.com/computer/database+management+%26+information+retrieval/book/978-1-4614-1893-1}, year = 2012 } @incollection{jaeschke2012challenges, abstract = {Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.}, added-at = {2012-02-09T09:26:57.000+0100}, address = {Berlin/Heidelberg}, affiliation = {Knowledge & Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany}, author = {Jäschke, Robert and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/27d41d332cccc3e7ba8e7dadfb7996337/hotho}, booktitle = {Recommender Systems for the Social Web}, doi = {10.1007/978-3-642-25694-3_3}, editor = {Pazos Arias, José J. and Fernández Vilas, Ana and Díaz Redondo, Rebeca P.}, interhash = {75b1a6f54ef54d0126d0616b5bf77563}, intrahash = {7d41d332cccc3e7ba8e7dadfb7996337}, isbn = {978-3-642-25694-3}, keywords = {2012 bookmarking challenge collaborative dc09 discovery folksonomy myown recommender rsdc08 social tagging}, pages = {65--87}, publisher = {Springer}, series = {Intelligent Systems Reference Library}, title = {Challenges in Tag Recommendations for Collaborative Tagging Systems}, url = {http://dx.doi.org/10.1007/978-3-642-25694-3_3}, volume = 32, year = 2012 } @incollection{jaeschke2012challenges, abstract = {Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.}, added-at = {2012-02-06T14:59:32.000+0100}, address = {Berlin/Heidelberg}, affiliation = {Knowledge & Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany}, author = {Jäschke, Robert and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/27d41d332cccc3e7ba8e7dadfb7996337/stumme}, booktitle = {Recommender Systems for the Social Web}, doi = {10.1007/978-3-642-25694-3_3}, editor = {Pazos Arias, José J. and Fernández Vilas, Ana and Díaz Redondo, Rebeca P.}, interhash = {75b1a6f54ef54d0126d0616b5bf77563}, intrahash = {7d41d332cccc3e7ba8e7dadfb7996337}, isbn = {978-3-642-25694-3}, keywords = {2012 bookmarking challenge collaborative dc09 discovery folksonomy myown recommender rsdc08 social tagging}, pages = {65--87}, publisher = {Springer}, series = {Intelligent Systems Reference Library}, title = {Challenges in Tag Recommendations for Collaborative Tagging Systems}, url = {http://dx.doi.org/10.1007/978-3-642-25694-3_3}, volume = 32, year = 2012 } @incollection{jaeschke2012challenges, abstract = {Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.}, added-at = {2012-02-06T14:04:20.000+0100}, address = {Berlin/Heidelberg}, affiliation = {Knowledge & Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany}, author = {Jäschke, Robert and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/27d41d332cccc3e7ba8e7dadfb7996337/dbenz}, booktitle = {Recommender Systems for the Social Web}, doi = {10.1007/978-3-642-25694-3_3}, editor = {Pazos Arias, José J. and Fernández Vilas, Ana and Díaz Redondo, Rebeca P.}, interhash = {75b1a6f54ef54d0126d0616b5bf77563}, intrahash = {7d41d332cccc3e7ba8e7dadfb7996337}, isbn = {978-3-642-25694-3}, keywords = {2012 challenge collaborative recommendation tagging}, pages = {65--87}, publisher = {Springer}, series = {Intelligent Systems Reference Library}, title = {Challenges in Tag Recommendations for Collaborative Tagging Systems}, url = {http://dx.doi.org/10.1007/978-3-642-25694-3_3}, volume = 32, year = 2012 } @incollection{jaeschke2012challenges, abstract = {Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.}, added-at = {2012-02-06T14:02:41.000+0100}, address = {Berlin/Heidelberg}, affiliation = {Knowledge & Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany}, author = {Jäschke, Robert and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/2b645572f4c635b2d674126f26d4303d6/sdo}, booktitle = {Recommender Systems for the Social Web}, doi = {10.1007/978-3-642-25694-3_3}, editor = {Kacprzyk, Janusz and Jain, Lakhmi C.}, interhash = {75b1a6f54ef54d0126d0616b5bf77563}, intrahash = {b645572f4c635b2d674126f26d4303d6}, isbn = {978-3-642-25694-3}, keywords = {challenge collaborative recommendation system tagging}, pages = {65--87}, publisher = {Springer}, series = {Intelligent Systems Reference Library}, title = {Challenges in Tag Recommendations for Collaborative Tagging Systems}, url = {http://dx.doi.org/10.1007/978-3-642-25694-3_3}, volume = 32, year = 2012 } @incollection{jaeschke2012challenges, abstract = {Originally introduced by social bookmarking systems, collaborative tagging, or social tagging, has been widely adopted by many web-based systems like wikis, e-commerce platforms, or social networks. Collaborative tagging systems allow users to annotate resources using freely chosen keywords, so called tags . Those tags help users in finding/retrieving resources, discovering new resources, and navigating through the system. The process of tagging resources is laborious. Therefore, most systems support their users by tag recommender components that recommend tags in a personalized way. The Discovery Challenges 2008 and 2009 of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) tackled the problem of tag recommendations in collaborative tagging systems. Researchers were invited to test their methods in a competition on datasets from the social bookmark and publication sharing system BibSonomy. Moreover, the 2009 challenge included an online task where the recommender systems were integrated into BibSonomy and provided recommendations in real time. In this chapter we review, evaluate and summarize the submissions to the two Discovery Challenges and thus lay the groundwork for continuing research in this area.}, added-at = {2012-02-06T13:47:57.000+0100}, address = {Berlin/Heidelberg}, affiliation = {Knowledge & Data Engineering Group, University of Kassel, Wilhelmshöher Allee 73, 34121 Kassel, Germany}, author = {Jäschke, Robert and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/27d41d332cccc3e7ba8e7dadfb7996337/jaeschke}, booktitle = {Recommender Systems for the Social Web}, doi = {10.1007/978-3-642-25694-3_3}, editor = {Pazos Arias, José J. and Fernández Vilas, Ana and Díaz Redondo, Rebeca P.}, interhash = {75b1a6f54ef54d0126d0616b5bf77563}, intrahash = {7d41d332cccc3e7ba8e7dadfb7996337}, isbn = {978-3-642-25694-3}, keywords = {2012 bookmarking challenge collaborative dc09 discovery folksonomy myown recommender rsdc08 social tagging}, pages = {65--87}, publisher = {Springer}, series = {Intelligent Systems Reference Library}, title = {Challenges in Tag Recommendations for Collaborative Tagging Systems}, url = {http://dx.doi.org/10.1007/978-3-642-25694-3_3}, volume = 32, year = 2012 } @article{Atzmueller2011a, abstract = {Conferator is a novel social conference system that provides the management of social interactions and context information in ubiquitous and social environments. Using RFID and social networking technology, Conferator provides the means for effective management of personal contacts and according conference information before, during and after a conference. We describe the system in detail, before we analyze and discuss results of a typical application of the Conferator system.}, added-at = {2012-01-19T15:57:22.000+0100}, address = {München}, author = {Atzmueller, Martin and Benz, Dominik and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Macek, Bjoern Elmar and Mitzlaff, Folke and Scholz, Christoph and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/2b96a6cf5d9999ca9063b7d7cd229e50d/enitsirhc}, doi = {10.1524/itit.2011.0631}, interhash = {e57bff1f73b74e6f1fe79e4b40956c35}, intrahash = {b96a6cf5d9999ca9063b7d7cd229e50d}, issn = {1611-2776}, journal = {Information Technology}, keywords = {rfid social 2011 myown computing conference ubiquitous network conferator}, month = may, number = 3, pages = {101--107}, publisher = {Oldenbourg Wissenschaftsverlag}, title = {Enhancing Social Interactions at Conferences}, url = {http://www.oldenbourg-link.com/doi/abs/10.1524/itit.2011.0631}, vgwort = {22}, volume = 53, year = 2011 } @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.}, added-at = {2012-01-19T12:34:45.000+0100}, address = {Berlin / Heidelberg}, author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Krause, Beate and Mitzlaff, Folke and Schmitz, Christoph and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/2c9437d5ec56ba949f533aeec00f571e3/nosebrain}, doi = {10.1007/s00778-010-0208-4}, interhash = {57fe43734b18909a24bf5bf6608d2a09}, intrahash = {c9437d5ec56ba949f533aeec00f571e3}, issn = {1066-8888}, journal = {The VLDB Journal}, keywords = {bibsonomy bookmark publication sharing social system}, month = dec, number = 6, pages = {849--875}, publisher = {Springer}, title = {The Social Bookmark and Publication Management System BibSonomy}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2010social.pdf}, volume = 19, year = 2010 } @inproceedings{Halle:2010, abstract = {The PUMA project fosters the Open Access movement und aims at a better support of the researcher’s publication work. PUMA stands for an integrated solution, where the upload of a publication results automatically in an update of both the personal and institutional homepage, the creation of an entry in a social bookmarking systems like BibSonomy, an entry in the academic reporting system of the university, and its publication in the institutional repository. In this poster, we present the main features of our solution. }, added-at = {2012-01-17T14:43:45.000+0100}, author = {Benz, Dominik and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd and Halle, Axel and Lima-Gerlach, Angela Sanches and Steenweg, Helge and Stefani, Sven}, biburl = {http://www.bibsonomy.org/bibtex/2792ef6888aaf686f744eaa414260bc43/stefani}, booktitle = {Proceedings of the 14. European Conference on Research and Advanced Technology for Digital Libraries }, doi = {10.1007}, ean = {978-3-642-15464-5}, interhash = {6769f676a73338ca4a431d47f2f5d3ff}, intrahash = {792ef6888aaf686f744eaa414260bc43}, isbn = {978-3-642-15464-5}, keywords = {Academic Management OpenAccess PUMA Publication myown}, pages = {417-420}, title = {Academic Publication Management with PUMA - collect, organize and share publications}, volume = {6273/2010}, year = 2010 } @inproceedings{hotho2006information, 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. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies,called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to findcommunities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset.}, added-at = {2012-01-17T10:20:59.000+0100}, address = {Heidelberg}, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/23c301945817681d637ee43901c016939/janus235}, booktitle = {The Semantic Web: Research and Applications}, editor = {Sure, York and Domingue, John}, file = {hotho2006information.pdf:hotho2006information.pdf:PDF}, groups = {public}, interhash = {10ec64d80b0ac085328a953bb494fb89}, intrahash = {3c301945817681d637ee43901c016939}, keywords = {folkrank folksonomies ranking}, month = {June}, pages = {411-426}, pdf = {hotho2006information.pdf}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {Information Retrieval in Folksonomies: Search and Ranking}, username = {dbenz}, volume = 4011, year = 2006 } @article{atzmueller2011enhancing, added-at = {2012-01-04T11:31:59.000+0100}, author = {Atzmüller, Martin and Benz, Dominik and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Macek, Bjoern Elmar and Mitzlaff, Folke and Scholz, Christoph and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/21ceba87cd6bc52faac36247a0c9f52a8/stumme}, ee = {http://dx.doi.org/10.1524/itit.2011.0631}, interhash = {39485536536e75b48c275c7f04df1776}, intrahash = {1ceba87cd6bc52faac36247a0c9f52a8}, journal = {it - Information Technology}, keywords = {2011 COMMUNE conferator itegpub myown rfid sociopatterns}, number = 3, pages = {101-107}, title = {Enhancing Social Interactions at Conferences.}, url = {http://dblp.uni-trier.de/db/journals/it/it53.html#AtzmullerBDHJMMSS11}, volume = 53, year = 2011 } @incollection{marinho2011social, abstract = {The new generation of Web applications known as (STS) is successfully established and poised for continued growth. STS are open and inherently social; features that have been proven to encourage participation. But while STS bring new opportunities, they revive old problems, such as information overload. Recommender Systems are well known applications for increasing the level of relevant content over the noise that continuously grows as more and more content becomes available online. In STS however, we face new challenges. Users are interested in finding not only content, but also tags and even other users. Moreover, while traditional recommender systems usually operate over 2-way data arrays, STS data is represented as a third-order tensor or a hypergraph with hyperedges denoting (user, resource, tag) triples. In this chapter, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve STS.We describe (a) novel facets of recommenders for STS, such as user, resource, and tag recommenders, (b) new approaches and algorithms for dealing with the ternary nature of STS data, and (c) recommender systems deployed in real world STS. Moreover, a concise comparison between existing works is presented, through which we identify and point out new research directions.}, added-at = {2012-01-04T11:31:34.000+0100}, address = {New York}, author = {Balby Marinho, Leandro and Nanopoulos, Alexandros and Schmidt-Thieme, Lars and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd and Symeonidis, Panagiotis}, biburl = {http://www.bibsonomy.org/bibtex/2708be7b5c269bd3a9d3d2334f858d52d/stumme}, booktitle = {Recommender Systems Handbook}, doi = {10.1007/978-0-387-85820-3_19}, editor = {Ricci, Francesco and Rokach, Lior and Shapira, Bracha and Kantor, Paul B.}, interhash = {2d4afa6f7fb103ccc166c9c5d629cdd1}, intrahash = {708be7b5c269bd3a9d3d2334f858d52d}, isbn = {978-0-387-85820-3}, keywords = {2011 collaborative itegpub myown recommender social tagging}, pages = {615--644}, publisher = {Springer}, title = {Social Tagging Recommender Systems}, url = {http://dx.doi.org/10.1007/978-0-387-85820-3_19}, year = 2011 } @article{martin2011enhancing, added-at = {2012-01-04T11:20:30.000+0100}, author = {Atzmueller, Martin and Benz, Dominik and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Macek, Bjoern Elmar and Mitzlaff, Folke and Scholz, Christoph and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/21dc34c1620c45a9bbd548bb73f989aea/stumme}, booktitle = {it - Information Technology}, comment = {doi: 10.1524/itit.2011.0631}, doi = {10.1524/itit.2011.0631}, interhash = {e57bff1f73b74e6f1fe79e4b40956c35}, intrahash = {1dc34c1620c45a9bbd548bb73f989aea}, issn = {16112776}, journal = {it - Information Technology}, keywords = {2011 conferator conference conferences interactions itegpub journal myown}, month = may, number = 3, pages = {101--107}, publisher = {Oldenbourg Wissenschaftsverlag GmbH}, title = {Enhancing Social Interactions at Conferences}, url = {http://dx.doi.org/10.1524/itit.2011.0631}, volume = 53, year = 2011 } @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.}, added-at = {2011-12-16T09:47:58.000+0100}, 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}, biburl = {http://www.bibsonomy.org/bibtex/25eb699b2e53803ca9e5fadf22d8b5966/victorinostar}, description = {SpringerLink - The VLDB Journal, Volume 19, Number 6}, doi = {10.1007/s00778-010-0208-4}, interhash = {57fe43734b18909a24bf5bf6608d2a09}, intrahash = {5eb699b2e53803ca9e5fadf22d8b5966}, issn = {1066-8888}, issue = {6}, journal = {The VLDB Journal}, keyword = {Computer Science}, keywords = {bibsonomy level_variation lucene p-core polysemy relatedness serendipitous_browsing similarity synonymy}, 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 } @article{martin2011enhancing, added-at = {2011-12-13T17:11:40.000+0100}, author = {Atzmueller, Martin and Benz, Dominik and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Macek, Bjoern Elmar and Mitzlaff, Folke and Scholz, Christoph and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/21dc34c1620c45a9bbd548bb73f989aea/hotho}, booktitle = {it - Information Technology}, comment = {doi: 10.1524/itit.2011.0631}, doi = {10.1524/itit.2011.0631}, interhash = {e57bff1f73b74e6f1fe79e4b40956c35}, intrahash = {1dc34c1620c45a9bbd548bb73f989aea}, issn = {16112776}, journal = {it - Information Technology}, keywords = {2011 conferator conference enhancing journal myown social}, month = may, number = 3, pages = {101--107}, publisher = {Oldenbourg Wissenschaftsverlag GmbH}, title = {Enhancing Social Interactions at Conferences}, url = {http://dx.doi.org/10.1524/itit.2011.0631}, volume = 53, year = 2011 } @article{martin2011enhancing, added-at = {2011-12-13T14:58:01.000+0100}, author = {Atzmueller, Martin and Benz, Dominik and Doerfel, Stephan and Hotho, Andreas and Jäschke, Robert and Macek, Bjoern Elmar and Mitzlaff, Folke and Scholz, Christoph and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/21dc34c1620c45a9bbd548bb73f989aea/dbenz}, booktitle = {it - Information Technology}, comment = {doi: 10.1524/itit.2011.0631}, doi = {10.1524/itit.2011.0631}, interhash = {e57bff1f73b74e6f1fe79e4b40956c35}, intrahash = {1dc34c1620c45a9bbd548bb73f989aea}, issn = {16112776}, journal = {it - Information Technology}, keywords = {2011 conferator journal lwa myown peerradar talkradar}, month = may, number = 3, pages = {101--107}, publisher = {Oldenbourg Wissenschaftsverlag GmbH}, title = {Enhancing Social Interactions at Conferences}, url = {http://dx.doi.org/10.1524/itit.2011.0631}, volume = 53, year = 2011 } @inproceedings{schmitz2006mining, abstract = {Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.}, added-at = {2011-12-13T08:38:34.000+0100}, address = {Heidelberg}, author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/2aacdba5a3ee5637d84459d7cf4a1eb05/beate}, booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.}, editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and {\v Z}iberna, A.}, interhash = {20650d852ca3b82523fcd8b63e7c12d7}, intrahash = {aacdba5a3ee5637d84459d7cf4a1eb05}, keywords = {association-rules semantics subsumption tagging}, month = {July}, pages = {261--270}, publisher = {Springer}, series = {Studies in Classification, Data Analysis, and Knowledge Organization}, title = {Mining Association Rules in Folksonomies}, year = 2006 } @inproceedings{conf/kont/IlligHJS07, added-at = {2011-12-06T00:00:00.000+0100}, author = {Illig, Jens and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd}, biburl = {http://www.bibsonomy.org/bibtex/24bd942334cefb0017b7e5c0eb2015877/dblp}, booktitle = {KONT/KPP}, crossref = {conf/kont/2007}, editor = {Wolff, Karl Erich and Palchunov, Dmitry E. and Zagoruiko, Nikolay G. and Andelfinger, Urs}, ee = {http://dx.doi.org/10.1007/978-3-642-22140-8_9}, interhash = {52a10dc852047ce9d0f3b61114cf6c8e}, intrahash = {4bd942334cefb0017b7e5c0eb2015877}, isbn = {978-3-642-22139-2}, keywords = {dblp}, pages = {136-149}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {A Comparison of Content-Based Tag Recommendations in Folksonomy Systems.}, url = {http://dblp.uni-trier.de/db/conf/kont/kont2007.html#IlligHJS07}, volume = 6581, year = 2007 } @incollection{marinho2011social, abstract = {The new generation of Web applications known as (STS) is successfully established and poised for continued growth. STS are open and inherently social; features that have been proven to encourage participation. But while STS bring new opportunities, they revive old problems, such as information overload. Recommender Systems are well known applications for increasing the level of relevant content over the “noise” that continuously grows as more and more content becomes available online. In STS however, we face new challenges. Users are interested in finding not only content, but also tags and even other users. Moreover, while traditional recommender systems usually operate over 2-way data arrays, STS data is represented as a third-order tensor or a hypergraph with hyperedges denoting (user, resource, tag) triples. In this chapter, we survey the most recent and state-of-the-art work about a whole new generation of recommender systems built to serve STS.We describe (a) novel facets of recommenders for STS, such as user, resource, and tag recommenders, (b) new approaches and algorithms for dealing with the ternary nature of STS data, and (c) recommender systems deployed in real world STS. Moreover, a concise comparison between existing works is presented, through which we identify and point out new research directions.}, added-at = {2011-12-05T21:07:20.000+0100}, affiliation = {Information Systems and Machine Learning Lab (ISMLL), University of Hildesheim, Marienburger Platz 22, 31141 Hildesheim, Germany}, author = {Marinho, Leandro Balby and Nanopoulos, Alexandros and Schmidt-Thieme, Lars and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd and Symeonidis, Panagiotis}, biburl = {http://www.bibsonomy.org/bibtex/2708be7b5c269bd3a9d3d2334f858d52d/beate}, booktitle = {Recommender Systems Handbook}, description = {SpringerLink - Export Citation}, doi = {10.1007/978-0-387-85820-3_19}, editor = {Ricci, Francesco and Rokach, Lior and Shapira, Bracha and Kantor, Paul B.}, interhash = {2d4afa6f7fb103ccc166c9c5d629cdd1}, intrahash = {708be7b5c269bd3a9d3d2334f858d52d}, isbn = {978-0-387-85820-3}, keyword = {Computer Science}, keywords = {recommender tagging}, pages = {615-644}, publisher = {Springer US}, title = {Social Tagging Recommender Systems}, url = {http://dx.doi.org/10.1007/978-0-387-85820-3_19}, year = 2011 }