@inproceedings{Scholz:2012:PHC:2411131.2411662,
  abstract = {While the analysis of online social networks is a prominent research topic, offline real-world networks are still not covered extensively. However, their analysis can provide important insights into human behavior. In this paper, we analyze influence factors for link prediction in human contact networks. Specifically, we consider the prediction of new links, and extend it to the analysis of recurring links. Furthermore, we consider the impact of stronger ties for the prediction. The results and insights of the analysis are a first step onto predictability applications for human contact networks.},
  acmid = {2411662},
  address = {Washington, DC, USA},
  author = {Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
  booktitle = {Proceedings of the 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust},
  doi = {10.1109/SocialCom-PASSAT.2012.49},
  interhash = {9bc5d42018dbe8b926be214190258b3c},
  intrahash = {b8771cc1fc02b5bb679c4a293eae517d},
  isbn = {978-0-7695-4848-7},
  numpages = {10},
  pages = {312--321},
  publisher = {IEEE Computer Society},
  series = {SOCIALCOM-PASSAT '12},
  title = {On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties},
  url = {http://dx.doi.org/10.1109/SocialCom-PASSAT.2012.49},
  year = 2012
}

@inproceedings{mueller-2012,
  abstract = {The connection of ubiquitous and social computing is an emerging research
 area which is combining two prominent areas of computer science.
 In this paper, we tackle this topic from different angles: We describe
 data mining methods for ubiquitous and social data, specifically
 focusing on physical and social activities, and provide exemplary
 analysis results. Furthermore, we give an overview on the Ubicon
 platform which provides a framework for the creation and hosting
 of ubiquitous and social applications for diverse tasks and projects.
 Ubicon features the collection and analysis of both physical and
 social activities of users for enabling inter-connected applications
 in ubiquitous and social contexts. We summarize three real-world
 systems built on top of Ubicon, and exemplarily discuss the according
 mining and analysis aspects.},
  address = {Washington, DC, USA},
  author = {Atzmueller, Martin and Becker, Martin and Doerfel, Stephan and Kibanov, Mark and Hotho, Andreas and Macek, Björn-Elmar and Mitzlaff, Folke and Mueller, Juergen and Scholz, Christoph and Stumme, Gerd},
  booktitle = {IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2012, Besançon, France, 20-23 November, 2012},
  interhash = {a2695fd9fe6e76b252edbd42d72b34ad},
  intrahash = {90847b1d969ac1ed1f4c8d7146416619},
  publisher = {IEEE},
  title = {Ubicon: Observing Social and Physical Activities},
  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.},
  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.},
  doi = {10.1007/978-1-4614-1894-8},
  interhash = {0bb7f0588cd690d67cc73e219a3a24fa},
  intrahash = {87d6883ebd98e8810be45d7e7e4ade96},
  isbn = {978-1-4614-1893-1},
  month = feb,
  publisher = {Springer},
  series = {SpringerBriefs in Electrical and Computer Engineering},
  title = {Recommender Systems for Social Tagging Systems},
  url = {http://link.springer.com/book/10.1007/978-1-4614-1894-8},
  year = 2012
}

@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
}

@incollection{BAESSG:12,
  abstract = {To facilitate user-centered software engineering, developers need an easy to grasp understanding of the user. The use of personas helps to keep specific user needs in mind during the design process. Technology acceptance is of particular interest for the design of innovative applications previously unknown to potential users. Therefore, our research focuses on defining a typology of relevant user characteristics with respect to technology acceptance and transferring those findings to the description of personas. The presented work focuses on the statistical relationship between technology acceptance and personality. We apply sub-group discovery as a statistical tool. Based on the statistically derived subgroups and patterns we define the mentioned personas to help developers to understand different forms of technology acceptance. By integrating the specifically defined personas into existing methods in the field of software engineering the feasibility of the presented approach is demonstrated.},
  address = {Heidelberg, Germany},
  author = {Behrenbruch, Kay and Atzmueller, Martin and Evers, Christoph and Schmidt, Ludger and Stumme, Gerd and Geihs, Kurt},
  booktitle = {Human-Centred Software Engineering},
  interhash = {1e609af1021c5acbb5db78444c52a9e9},
  intrahash = {847830846b80d4507aa4b93d1c8deb83},
  pages = {259--266 },
  publisher = {Springer},
  series = {LNCS},
  title = {{A Personality Based Design Approach Using Subgroup Discovery}},
  volume = 7623,
  year = 2012
}

@inproceedings{doerfel2012publication,
  abstract = {We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.
},
  address = {Berlin/Heidelberg},
  author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd},
  booktitle = {ICFCA 2012},
  editor = {Domenach, F. and Ignatov, D.I. and Poelmans, J.},
  interhash = {f34f31e8dd1e07b1b0a5ab688f10084a},
  intrahash = {0ac1296af204a499490bf61a48d03e48},
  pages = {77--95},
  publisher = {Springer},
  series = {Lecture Notes in Artificial Intelligence},
  title = {Publication Analysis of the Formal Concept Analysis Community},
  url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf},
  volume = 7278,
  year = 2012
}

@inproceedings{SAS:12,
  address = {Boston, MA, USA},
  author = {Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
  booktitle = {Proc. Fourth ASE/IEEE International Conference on Social Computing (SocialCom)},
  interhash = {9bc5d42018dbe8b926be214190258b3c},
  intrahash = {be5ae4b92170e7c595f5fdcac15b4786},
  publisher = {IEEE Computer Society},
  title = {{On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties}},
  url = {http://www.kde.cs.uni-kassel.de/atzmueller/paper/scholz-on-f2f-predictability-socialcom-2012.pdf},
  year = 2012
}

@inproceedings{doerfel2012leveraging,
  abstract = {The ever-growing flood of new scientific articles requires novel retrieval mechanisms. One means for mitigating this instance of the information overload phenomenon are collaborative tagging systems, that allow users to select, share and annotate references to publications. These systems employ recommendation algorithms to present to their users personalized lists of interesting and relevant publications. In this paper we analyze different ways to incorporate social data and metadata from collaborative tagging systems into the graph-based ranking algorithm FolkRank to utilize it for recommending scientific articles to users of the social bookmarking system BibSonomy. We compare the results to those of Collaborative Filtering, which has previously been applied for resource recommendation.},
  address = {New York, NY, USA},
  author = {Doerfel, Stephan and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd},
  booktitle = {Proceedings of the 4th ACM RecSys workshop on Recommender systems and the social web},
  doi = {10.1145/2365934.2365937},
  interhash = {beb2c81daf975eeed6e01e1b412196b1},
  intrahash = {64bf590675a833770b7d284871435a8d},
  isbn = {978-1-4503-1638-5},
  location = {Dublin, Ireland},
  month = sep,
  pages = {9--16},
  publisher = {ACM},
  title = {Leveraging Publication Metadata and Social Data into FolkRank for Scientific Publication Recommendation },
  url = {http://doi.acm.org/10.1145/2365934.2365937},
  year = 2012
}

@inproceedings{mitzlaff2012namelings,
  author = {Mitzlaff, Folke and Stumme, Gerd},
  booktitle = {SocInfo},
  editor = {Aberer, Karl and Flache, Andreas and Jager, Wander and Liu, Ling and Tang, Jie and Guéret, Christophe},
  ee = {http://dx.doi.org/10.1007/978-3-642-35386-4_39},
  interhash = {2f803cd9938df1f11229f9180577a341},
  intrahash = {e2770a8535fca7cce582148703d8980a},
  isbn = {978-3-642-35385-7},
  pages = {531-534},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Namelings - Discover Given Name Relatedness Based on Data from the Social Web.},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/mitzlaff2012namelings.pdf},
  volume = 7710,
  year = 2012
}

@inproceedings{mitzlaff2012ranking,
  author = {Mitzlaff, Folke and Stumme, Gerd},
  booktitle = {Proceedings of the 1st ASE International Conference on Social Informatics},
  editor = {Marathe, Madhav and Contractor, Noshir},
  interhash = {339a7285bfb35e6f3eb1f22f98e818a3},
  intrahash = {c2f599000eaa568ed4d1b0b9d3f6fadd},
  pages = {185-191},
  publisher = {IEEE computer society},
  title = {Ranking Given Names},
  year = 2012
}

@inproceedings{MacekASS11,
  address = {Milwaukee, WI, USA, June 25-28, 2012},
  author = {Macek, Bjoern Elmar and Scholz, Christoph and Atzmueller, Martin and Stumme, Gerd},
  booktitle = {23rd ACM Conference on Hypertext and Social Media, HT '12},
  interhash = {5ccd00a47cae3a59c804ee294e127ee7},
  intrahash = {0295e33864389c0233f9dd0c8c16dafe},
  note = {Best Paper},
  pages = {245-254},
  publisher = {ACM},
  title = {Anatomy of a Conference},
  url = {http://dl.acm.org/citation.cfm?id=2309996},
  year = 2012
}

@incollection{ADHMS:12,
  address = {Heidelberg, Germany},
  alteditor = {Editor},
  author = {Atzmueller, Martin and Doerfel, Stephan and Hotho, Andreas and Mitzlaff, Folke and Stumme, Gerd},
  booktitle = {{Modeling and Mining Ubiquitous Social Media}},
  interhash = {4f1f4b515b01cc448a91b3e368deabad},
  intrahash = {d81d6f6ccdf3ff6572898d39c90e6354},
  publisher = {Springer Verlag},
  series = {LNAI},
  title = {Face-to-Face Contacts at a Conference: Dynamics of Communities and Roles},
  url = {http://www.kde.cs.uni-kassel.de/atzmueller/paper/atzmueller-face-to-face-contacts-dynamics-lnai-2012.pdf},
  volume = 7472,
  year = 2012
}

@article{mitzlaff2012relatedness,
  abstract = {As a result of the author's need for help in finding a given namefor the  unborn baby, nameling, a search engine for given names, based on data from the ``Social Web'' was born. Within less than six months, more than 35,000 users accessed nameling with more than 300,000 search requests, underpinning the relevance of the underlying research questions. The present work proposes a new approach for discovering relations among given names, based on co-occurrences within Wikipedia. In particular, the task of finding relevant names for a given search query is considered as a ranking task and the performance of different measures of relatedness among given names are evaluated with respect to nameling's actual usage data. We will show that a modification for the PageRank algorithm overcomes limitations imposed by global network characteristics to preferential PageRank computations. By publishing the considered usage data, the research community is stipulated for developing advanced recommendation systems and analyzing influencing factors for the choice of a given name.
},
  author = {Mitzlaff, Folke and Stumme, Gerd},
  interhash = {31f7605431c35592afa50e7a377ce999},
  intrahash = {63b13ff16093202c535e5aaac107e567},
  journal = {Human Journal},
  number = 4,
  pages = {205-217},
  publisher = {Academy of Science and Engineering},
  title = {Relatedness of Given Names},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/mitzlaff2012relatedness.pdf},
  volume = 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.},
  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},
  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},
  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
}