Publications - BibSonomy

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  Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning. Niebler, Thomas; Becker, Martin; Pölitz, Christian; Hotho, Andreas (2017).
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  @inproceedings{niebler2017learning_3, author = {Niebler, Thomas and Becker, Martin and Pölitz, Christian and Hotho, Andreas}, booktitle = {ISWC'17}, keywords = {semantics}, title = {Learning Semantic Relatedness from Human Feedback Using Relative Relatedness Learning}, year = 2017 }
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  Leveraging User-Interactions for Time-Aware Tag Recommendations. Zoller, Daniel; Doerfel, Stephan; Pölitz, Christian; Hotho, Andreas in {CEUR} Workshop Proceedings (2017).
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  For the popular task of tag recommendation, various (complex) approaches have been proposed. Recently however, research has focused on heuristics with low computational effort and particularly, a time-aware heuristic, called BLL, has been shown to compare well to various state-of-the-art methods. Here, we follow up on these results by presenting another time-aware approach leveraging user interaction data in an easily interpretable, on-the-fly computable approach that can successfully be combined with BLL. We investigate the influence of time as a parameter in that approach, and we demonstrate the effectiveness of the proposed method using two datasets from the popular public social tagging system BibSonomy.

  @inproceedings{zoller2017leveraging, abstract = {For the popular task of tag recommendation, various (complex) approaches have been proposed. Recently however, research has focused on heuristics with low computational effort and particularly, a time-aware heuristic, called BLL, has been shown to compare well to various state-of-the-art methods. Here, we follow up on these results by presenting another time-aware approach leveraging user interaction data in an easily interpretable, on-the-fly computable approach that can successfully be combined with BLL. We investigate the influence of time as a parameter in that approach, and we demonstrate the effectiveness of the proposed method using two datasets from the popular public social tagging system BibSonomy.}, author = {Zoller, Daniel and Doerfel, Stephan and Pölitz, Christian and Hotho, Andreas}, booktitle = {Proceedings of the Workshop on Temporal Reasoning in Recommender Systems}, keywords = {user}, series = {{CEUR} Workshop Proceedings}, title = {Leveraging User-Interactions for Time-Aware Tag Recommendations}, year = 2017 }

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  FolkTrails: Interpreting Navigation Behavior in a Social Tagging System. Niebler, Thomas; Becker, Martin; Zoller, Daniel; Doerfel, Stephan; Hotho, Andreas in CIKM ’16 (2016).
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  Social tagging systems have established themselves as a quick and easy way to organize information by annotating resources with tags. In recent work, user behavior in social tagging systems was studied, that is, how users assign tags, and consume content. However, it is still unclear how users make use of the navigation options they are given. Understanding their behavior and differences in behavior of different user groups is an important step towards assessing the effectiveness of a navigational concept and of improving it to better suit the users’ needs. In this work, we investigate navigation trails in the popular scholarly social tagging system BibSonomy from six years of log data. We discuss dynamic browsing behavior of the general user population and show that different navigational subgroups exhibit different navigational traits. Furthermore, we provide strong evidence that the semantic nature of the underlying folksonomy is an essential factor for explaining navigation.

  @inproceedings{niebler2016folktrails, abstract = {Social tagging systems have established themselves as a quick and easy way to organize information by annotating resources with tags. In recent work, user behavior in social tagging systems was studied, that is, how users assign tags, and consume content. However, it is still unclear how users make use of the navigation options they are given. Understanding their behavior and differences in behavior of different user groups is an important step towards assessing the effectiveness of a navigational concept and of improving it to better suit the users’ needs. In this work, we investigate navigation trails in the popular scholarly social tagging system BibSonomy from six years of log data. We discuss dynamic browsing behavior of the general user population and show that different navigational subgroups exhibit different navigational traits. Furthermore, we provide strong evidence that the semantic nature of the underlying folksonomy is an essential factor for explaining navigation.}, address = {New York, NY, USA}, author = {Niebler, Thomas and Becker, Martin and Zoller, Daniel and Doerfel, Stephan and Hotho, Andreas}, booktitle = {Proceedings of the 25th ACM International on Conference on Information and Knowledge Management}, keywords = {tagging}, publisher = {ACM}, series = {CIKM '16}, title = {FolkTrails: Interpreting Navigation Behavior in a Social Tagging System}, year = 2016 }
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  Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy. Zoller, Daniel; Doerfel, Stephan; Jäschke, Robert; Stumme, Gerd; Hotho, Andreas in Journal of Informetrics (2016). 10(3) 732–749.
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  In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.

  @article{zoller2016posted, abstract = {In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications. In this paper, we compare citations with metrics derived from users’ activities (altmetrics) in the popular social bookmarking system BibSonomy. Our analysis, using a corpus of more than 250,000 publications published before 2010, reveals that overall, citations and altmetrics in BibSonomy are mildly correlated. Furthermore, grouping publications by user-generated tags results in topic-homogeneous subsets that exhibit higher correlations with citations than the full corpus. We find that posts, exports, and visits of publications are correlated with citations and even bear predictive power over future impact. Machine learning classifiers predict whether the number of citations that a publication receives in a year exceeds the median number of citations in that year, based on the usage counts of the preceding year. In that setup, a Random Forest predictor outperforms the baseline on average by seven percentage points.}, author = {Zoller, Daniel and Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd and Hotho, Andreas}, journal = {Journal of Informetrics}, keywords = {tagging}, number = 3, pages = {732--749}, title = {Posted, Visited, Exported: Altmetrics in the Social Tagging System BibSonomy}, volume = 10, year = 2016 }
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  What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy. Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus in ACM Transactions on the Web (2016). 10(2) 14:1–14:32.
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  Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.

  @article{doerfel2016users, abstract = {Social tagging systems have established themselves as an important part in today’s web and have attracted the interest of our research community in a variety of investigations. Henceforth, several aspects of social tagging systems have been discussed and assumptions have emerged on which our community builds their work. Yet, testing such assumptions has been difficult due to the absence of suitable usage data in the past. In this work, we thoroughly investigate and evaluate four aspects about tagging systems, covering social interaction, retrieval of posted resources, the importance of the three different types of entities, users, resources, and tags, as well as connections between these entities’ popularity in posted and in requested content. For that purpose, we examine live server log data gathered from the real-world, public social tagging system BibSonomy. Our empirical results paint a mixed picture about the four aspects. While for some, typical assumptions hold to a certain extent, other aspects need to be reflected in a very critical light. Our observations have implications for the understanding of social tagging systems, and the way they are used on the web. We make the dataset used in this work available to other researchers.}, author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, journal = {ACM Transactions on the Web}, keywords = {user}, number = 2, pages = {14:1--14:32}, title = {What Users Actually do in a Social Tagging System: A Study of User Behavior in BibSonomy}, volume = 10, year = 2016 }

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  Modeling and Extracting Load Intensity Profiles. v. Kistowski, Jóakim; Nikolas, Herbst.; Zoller, Daniel; Kounev, Samuel; Hotho, Andreas (2015).
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  Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time. To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches.

  @inproceedings{vkistowski2015toappearmodeling, abstract = {Today’s system developers and operators face the challenge of creating software systems that make efficient use of dynamically allocated resources under highly variable and dynamic load profiles, while at the same time delivering reliable performance. Benchmarking of systems under these constraints is difficult, as state-of-the-art benchmarking frameworks provide only limited support for emulating such dynamic and highly vari- able load profiles for the creation of realistic workload scenarios. Industrial benchmarks typically confine themselves to workloads with constant or stepwise increasing loads. Alternatively, they support replaying of recorded load traces. Statistical load inten- sity descriptions also do not sufficiently capture concrete pattern load profile variations over time. To address these issues, we present the Descartes Load Intensity Model (DLIM). DLIM provides a modeling formalism for describing load intensity variations over time. A DLIM instance can be used as a compact representation of a recorded load intensity trace, providing a powerful tool for benchmarking and performance analysis. As manually obtaining DLIM instances can be time consuming, we present three different automated extraction methods, which also help to enable autonomous system analysis for self-adaptive systems. Model expressiveness is validated using the presented extraction methods. Extracted DLIM instances exhibit a median modeling error of 12.4% on average over nine different real-world traces covering between two weeks and seven months. Additionally, extraction methods perform orders of magnitude faster than existing time series decomposition approaches.}, author = {v. Kistowski, Jóakim and Nikolas, Herbst. and Zoller, Daniel and Kounev, Samuel and Hotho, Andreas}, booktitle = {Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)}, keywords = {project:bibsonomy}, title = {Modeling and Extracting Load Intensity Profiles}, year = 2015 }

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  Evaluating Assumptions about Social Tagging - {A} Study of User Behavior in BibSonomy. Doerfel, Stephan; Zoller, Daniel; Singer, Philipp; Niebler, Thomas; Hotho, Andreas; Strohmaier, Markus in {CEUR} Workshop Proceedings, T. Seidl, M. Hassani, C. Beecks (eds.) (2014). (Vol. 1226) 18–19.
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  @inproceedings{doerfel2014evaluating, author = {Doerfel, Stephan and Zoller, Daniel and Singer, Philipp and Niebler, Thomas and Hotho, Andreas and Strohmaier, Markus}, booktitle = {Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014.}, crossref = {DBLP:conf/lwa/2014}, editor = {Seidl, Thomas and Hassani, Marwan and Beecks, Christian}, keywords = {user}, pages = {18--19}, publisher = {CEUR-WS.org}, series = {{CEUR} Workshop Proceedings}, title = {Evaluating Assumptions about Social Tagging - {A} Study of User Behavior in BibSonomy}, volume = 1226, year = 2014 }

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  Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy. Krause, Beate; Lerch, Hana; Hotho, Andreas; Roßnagel, Alexander; Stumme, Gerd in Informatik Spektrum (2012). 35(1) 12–23.
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  @article{journals/insk/KrauseLHRS12, author = {Krause, Beate and Lerch, Hana and Hotho, Andreas and Roßnagel, Alexander and Stumme, Gerd}, journal = {Informatik Spektrum}, keywords = {tagging}, number = 1, pages = {12-23}, title = {Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy.}, volume = 35, year = 2012 }

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  Tagging data as implicit feedback for learning-to-rank. Bullock, Beate Navarro; Jäschke, Robert; Hotho, Andreas (2011).
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  @inproceedings{bullock2011tagging, author = {Bullock, Beate Navarro and Jäschke, Robert and Hotho, Andreas}, booktitle = {Proceedings of the ACM WebSci'11}, keywords = {social}, month = {June}, title = {Tagging data as implicit feedback for learning-to-rank}, year = 2011 }

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  The Social Bookmark and Publication Management System BibSonomy. Benz, Dominik; Hotho, Andreas; Jäschke, Robert; Krause, Beate; Mitzlaff, Folke; Schmitz, Christoph; Stumme, Gerd in The VLDB Journal (2010). 19(6) 849–875.
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  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.

  @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}, journal = {The VLDB Journal}, keywords = {vldb}, month = {dec}, number = 6, pages = {849--875}, publisher = {Springer}, title = {The Social Bookmark and Publication Management System BibSonomy}, volume = 19, year = 2010 }
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  {Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{\"u}r Wissenschaftler}. Hotho, Andreas; Benz, Dominik; Eisterlehner, Folke; J{\"a}schke, Robert; Krause, Beate; Schmitz, Christoph; Stumme, Gerd in HMD -- Praxis der Wirtschaftsinformatik (2010). Heft 271 47–58.
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  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.

  @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}, journal = {HMD -- Praxis der Wirtschaftsinformatik}, keywords = {web}, month = {#feb#}, pages = {47-58}, title = {{Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{\"u}r Wissenschaftler}}, volume = {Heft 271}, year = 2010 }

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  Social Bookmarking am Beispiel BibSonomy. Hotho, Andreas; Jäschke, Robert; Benz, Dominik; Grahl, Miranda; Krause, Beate; Schmitz, Christoph; Stumme, Gerd in Social Semantic Web, A. Blumauer, T. Pellegrini (eds.) (2009). 363–391.
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  BibSonomy ist ein kooperatives Verschlagwortungssystem (Social Bookmarking System), betrieben vom Fachgebiet Wissensverarbeitung der Universität Kassel. Es erlaubt das Speichern und Organisieren von Web-Lesezeichen und Metadaten für wissenschaftlichePublikationen. In diesem Beitrag beschreiben wir die von BibSonomy bereitgestellte Funktionalität, die dahinter stehende Architektursowie das zugrunde liegende Datenmodell. Ferner erläutern wir Anwendungsbeispiele und gehen auf Methoden zur Analyse der in BibSonomy und ähnlichen Systemen enthaltenen Daten ein.

  @incollection{hotho2008social, abstract = {BibSonomy ist ein kooperatives Verschlagwortungssystem (Social Bookmarking System), betrieben vom Fachgebiet Wissensverarbeitung der Universität Kassel. Es erlaubt das Speichern und Organisieren von Web-Lesezeichen und Metadaten für wissenschaftlichePublikationen. In diesem Beitrag beschreiben wir die von BibSonomy bereitgestellte Funktionalität, die dahinter stehende Architektursowie das zugrunde liegende Datenmodell. Ferner erläutern wir Anwendungsbeispiele und gehen auf Methoden zur Analyse der in BibSonomy und ähnlichen Systemen enthaltenen Daten ein.}, address = {Berlin, Heidelberg}, author = {Hotho, Andreas and Jäschke, Robert and Benz, Dominik and Grahl, Miranda and Krause, Beate and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Social Semantic Web}, chapter = 18, editor = {Blumauer, Andreas and Pellegrini, Tassilo}, keywords = {tagorapub}, pages = {363--391}, publisher = {Springer}, series = {X.media.press}, title = {Social Bookmarking am Beispiel BibSonomy}, year = 2009 }
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  Testing and Evaluating Tag Recommenders in a Live System. Jäschke, Robert; Eisterlehner, Folke; Hotho, Andreas; Stumme, Gerd D. Benz, F. Janssen (eds.) (2009). 369–372.
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  The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.

  @inproceedings{jaeschke2009testingKDML, abstract = {The challenge to provide tag recommendations for collaborative tagging systems has attracted quite some attention of researchers lately. However, most research focused on evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. Furthermore, this paper presents an evaluation of two exemplarily deployed recommendation methods, demonstrating the power of the framework.}, author = {Jäschke, Robert and Eisterlehner, Folke and Hotho, Andreas and Stumme, Gerd}, booktitle = {RecSys '09: Proceedings of the third ACM Conference on Recommender Systems}, editor = {Benz, Dominik and Janssen, Frederik}, keywords = {taggingsurvey}, pages = {369--372}, title = {Testing and Evaluating Tag Recommenders in a Live System}, year = 2009 }
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  ECML PKDD Discovery Challenge 2009 (DC09) Eisterlehner, Folke; Hotho, Andreas; Jäschke, Robert in CEUR-WS.org (2009). (Vol. 497)
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  @proceedings{eisterlehner2009ecmlpkdd, editor = {Eisterlehner, Folke and Hotho, Andreas and Jäschke, Robert}, keywords = {project:bibsonomy}, month = {sep}, series = {CEUR-WS.org}, title = {ECML PKDD Discovery Challenge 2009 (DC09)}, volume = 497, year = 2009 }
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  Who are the Spammers? Understandable Local Patterns for Concept Description. Atzmueller, Martin; Lemmerich, Florian; Krause, Beate; Hotho, Andreas (2009).
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  @inproceedings{atze09, address = {Krakow, Poland}, author = {Atzmueller, Martin and Lemmerich, Florian and Krause, Beate and Hotho, Andreas}, booktitle = {7th Conference on Computer Methods and Systems}, keywords = {subgroup}, month = {November}, note = {ISBN 83-916420-5-4}, title = {Who are the Spammers? Understandable Local Patterns for Concept Description}, year = 2009 }

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  Tag Recommendations in Folksonomies. Jäschke, Robert; Marinho, Leandro; Hotho, Andreas; Schmidt-Thieme, Lars; Stumme, Gerd A. Hinneburg (ed.) (2007). 13–20.
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  @inproceedings{jaeschke07tagKdml, author = {Jäschke, Robert and Marinho, Leandro and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd}, booktitle = {Workshop Proceedings of Lernen - Wissensentdeckung - Adaptivität (LWA 2007)}, editor = {Hinneburg, Alexander}, keywords = {social}, month = {sep}, pages = {13-20}, publisher = {Martin-Luther-Universität Halle-Wittenberg}, title = {Tag Recommendations in Folksonomies}, year = 2007 }
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  Tag Recommendations in Folksonomies. Jäschke, Robert; Marinho, Leandro Balby; Hotho, Andreas; Schmidt-Thieme, Lars; Stumme, Gerd in Lecture Notes in Computer Science, J. N. Kok, J. Koronacki, R. L. de Mántaras, S. Matwin, D. Mladenic, A. Skowron (eds.) (2007). (Vol. 4702) 506–514.
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  @inproceedings{jaschke07recommender, author = {Jäschke, Robert and Marinho, Leandro Balby and Hotho, Andreas and Schmidt-Thieme, Lars and Stumme, Gerd}, booktitle = {Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings}, editor = {Kok, Joost N. and Koronacki, Jacek and de Mántaras, Ramon López and Matwin, Stan and Mladenic, Dunja and Skowron, Andrzej}, keywords = {taggingsurvey}, pages = {506-514}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {Tag Recommendations in Folksonomies}, volume = 4702, year = 2007 }
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  Analysis of the Publication Sharing Behaviour in {BibSonomy}. Jäschke, Robert; Hotho, Andreas; Schmitz, Christoph; Stumme, Gerd in LNCS (2007). (Vol. 4604)
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  BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.

  @inproceedings{jaeschke2007analysis, abstract = {BibSonomy is a web-based social resource sharing system which allows users to organise and share bookmarks and publications in a collaborative manner. In this paper we present the system, followed by a description of the insights in the structure of its bibliographic data that we gained by applying techniques we developed in the area of Formal Concept Analysis.}, address = {Sheffield, England}, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Proceedings of the 15th International Conference on Conceptual Structures}, keywords = {trias}, month = {July}, series = {LNCS}, title = {Analysis of the Publication Sharing Behaviour in {BibSonomy}}, volume = 4604, year = 2007 }
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  Network Properties of Folksonomies. Schmitz, Christoph; Grahl, Miranda; Hotho, Andreas; Stumme, Gerd; Catutto, Ciro; Baldassarri, Andrea; Loreto, Vittorio; Servedio, Vito D. P. (2007).
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  @inproceedings{schmitz2007network, address = {Banff}, author = {Schmitz, Christoph and Grahl, Miranda and Hotho, Andreas and Stumme, Gerd and Catutto, Ciro and Baldassarri, Andrea and Loreto, Vittorio and Servedio, Vito D. P.}, booktitle = {Proc. WWW2007 Workshop ``Tagging and Metadata for Social Information Organization''}, keywords = {workshop}, month = {May}, title = {Network Properties of Folksonomies}, year = 2007 }

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  Information Retrieval in Folksonomies: Search and Ranking. Hotho, Andreas; Jäschke, Robert; Schmitz, Christoph; Stumme, Gerd in LNCS (2006). (Vol. 4011) 411–426.
  • [ BibTeX ]
  • [ URL ]
  • [ Download ]
  @inproceedings{hotho2006information, address = {Budva, Montenegro}, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Proceedings of the 3rd European Semantic Web Conference}, keywords = {summerschool}, month = {June}, pages = {411-426}, publisher = {Springer}, series = {LNCS}, title = {Information Retrieval in Folksonomies: Search and Ranking}, volume = 4011, year = 2006 }
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  Wege zur Entdeckung von Communities in Folksonomies. Jäschke, Robert; Hotho, Andreas; Schmitz, Christoph; Stumme, Gerd S. Braß, A. Hinneburg (eds.) (2006). 80–84.
  • [ BibTeX ]
  @inproceedings{jaeschke06wege, address = {Halle-Wittenberg}, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Proc. 18. Workshop Grundlagen von Datenbanken}, editor = {Braß, Stefan and Hinneburg, Alexander}, keywords = {project:bibsonomy}, month = {June}, pages = {80-84}, publisher = {Martin-Luther-Universität}, title = {Wege zur Entdeckung von Communities in Folksonomies}, year = 2006 }
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  {BibSonomy}: A Social Bookmark and Publication Sharing System. Hotho, Andreas; Jäschke, Robert; Schmitz, Christoph; Stumme, Gerd (2006). 87–102.
  • [ BibTeX ]
  • [ URL ]
  @inproceedings{hjss06bibsonomy, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Proceedings of the Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures}, keywords = {social}, pages = {87-102}, title = {{BibSonomy}: A Social Bookmark and Publication Sharing System}, year = 2006 }
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  Emergent Semantics in BibSonomy. Hotho, Andreas; Jäschke, Robert; Schmitz, Christoph; Stumme, Gerd (2006). (Vol. P-94)
  • [ BibTeX ]
  • [ URL ]
  @inproceedings{hotho2006emergent, address = {Dresden}, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, booktitle = {Proc. Workshop on Applications of Semantic Technologies, Informatik 2006}, keywords = {semantics}, month = {oct}, title = {Emergent Semantics in BibSonomy}, volume = {P-94}, year = 2006 }