BibSonomy publications for /user/hotho/2010Thu Jan 27 09:24:11 CET 2011Berlin / HeidelbergThe VLDB Journaldec6849--875The Social Bookmark and Publication Management System BibSonomy1920102010 bibsonomy myown publication social system tagging taggingsurvey 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.Wed Jan 26 16:56:55 CET 2011Berlin/HeidelbergProceedings of the European Conference on Research and Advanced Technology for Digital Libraries (ECDL) 2010417--420Lecture Notes in Computer ScienceAcademic Publication Management with PUMA - collect, organize and share publications627320102010 ecdl myown poster puma 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. Wed Jan 26 16:52:28 CET 2011KI 2010: Advances in Artificial Intelligence, 33rd Annual German Conference on AI40-47 LNAI 6359Local Adaptive Extraction of References20102010 ie myown references scholary The accurate extraction of scholarly reference information from scientific publications is essential for many useful applications like BibTeX management systems or citation analysis. Automatic extraction methods suffer from the heterogeneity of reference notation, no matter wether the extraction model was handcrafted or learnt from labeled data. However, references of the same paper or journal are usually homogeneous. We exploit this local consistency with a novel approach. Given some initial information from such a reference section, we try to derived generalized patterns. These patterns are used to create a local model of the current document. The local model helps to identify errors and to improve the extracted information incrementally during the extraction process. Our approach is implemented with handcrafted transformation rules working on a meta-level being able to correct the information independent of the applied layout style. The experimental results compete very well with the state of the art methods and show an extremely high performance on consistent reference sections. Wed Jan 26 16:29:56 CET 2011Barcelona, Spain{Proceedings of the 2010 Workshop on Mining Ubiquitous and Social Environments (MUSE 2010)}20102010 muse myown proceedings social ubiquitous workshop Wed Jan 26 16:28:11 CET 2011Barcelona, SpainProceedings of the Workshop on Mining Ubiquitous and Social Environments (MUSE2010)Community Assessment using Evidence Networks20102010 assessment bibsonomy community evidence myown networks Community mining is a prominent approach for identifying (user) communities in social and ubiquitous contexts. While there are a variety of methods for community mining and detection, the effective evaluation and validation of the mined communities is usually non-trivial. Often there is no evaluation data at hand in order to validate the discovered groups. This paper proposes evidence networks using implicit information for the evaluation of communities. The presented evaluation approach is based on the idea of reconstructing existing social structures for the assessment and evaluation of a given clustering. We analyze and compare the presented evidence networks using user data from the real-world social bookmarking application BibSonomy. The results indicate that the evidence networks reflect the relative rating of the explicit ones very well.Wed Jan 26 16:27:34 CET 2011HMD -- Praxis der Wirtschaftsinformatik#feb#47-58{Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{\"u}r Wissenschaftler}Heft 27120102.0 2010 bibsonomy bookmarking myown social tagging taggingsurvey web 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.Wed Jan 26 16:23:55 CET 2011Technical report (KIS), 2010-10{Proceedings of the LWA 2010 - Lernen, Wissen, Adaptivit\"at}20102010 lwa myown proceedings Wed Jan 26 16:23:12 CET 2011MultiMedia und Recht454-458Social Bookmarking-Systeme – die unerkannten Datensammler - Ungewollte personenbezogene Datenverabeitung?720102010 bibsonomy bookmarking datenschutz info2.0 myown social Tue Dec 14 12:09:05 CET 2010Berlin / HeidelbergIntelligent Information Access57-82Studies in Computational IntelligenceData Mining on Folksonomies30120102010 data folksonomies mining myown Social resource sharing systems are central elements of the Web 2.0 and use all the same kind of lightweight knowledge representation, called folksonomy. As these systems are easy to use, they attract huge masses of users. Data Mining provides methods to analyze data and to learn models which can be used to support users. The application and adaptation of known data mining algorithms to folksonomies with the goal to support the users of such systems and to extract valuable information with a special focus on the Semantic Web is the main target of this paper. In this work we give a short introduction into folksonomies with a focus on our own system BibSonomy. Based on the analysis we made on a large folksonomy dataset, we present the application of data mining algorithms on three different tasks, namely spam detection, ranking and recommendation. To bridge the gap between folksonomies and the Semantic Web, we apply association rule mining to extract relations and present a deeper analysis of statistical measures which can be used to extract tag relations. This approach is complemented by presenting two approaches to extract conceptualizations from folksonomies.Sun Oct 03 16:10:55 CEST 2010Kassel, GermanyProceedings of LWA2010 - Workshop-Woche: Lernen, Wissen {\&} Adaptivitaetlwa2010Conditional Random Fields For Local Adaptive Reference Extraction20102010 crf extraction information myown The accurate extraction of bibliographic information from scientific publications is an active field of research. Machine learning and sequence labeling approaches like Conditional Random Fields (CRF) are often applied for this reference extraction task, but still suffer from the ambiguity of reference notation. Reference sections apply a predefined style guide and contain only homogeneous references. Therefore, other references of the same paper or journal often provide evidence how the fields of a reference are correctly labeled. We propose a novel approach that exploits the similarities within a document. Our process model uses information of unlabeled documents directly during the extraction task in order to automatically adapt to the perceived style guide. This is implemented by changing the manifestation of the features for the applied CRF. The experimental results show considerable improvements compared to the common approach. We achieve an average F1 score of 96.7% and an instance accuracy of 85.4% on the test data set.Thu Jul 08 12:57:16 CEST 2010Web Semantics: Science, Services and Agents on the World Wide WebBridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0; The Future of Knowledge Dissemination: The Elsevier Grand Challenge for the Life Sciences2-395 - 96Bridging the Gap--Data Mining and Social Network Analysis for Integrating Semantic Web and Web 2.0820102010 data introduction mining myown network semantic social web Thu Jun 17 20:42:17 CEST 2010Raleigh, NC, USAProceedings of the 2nd Web Science Conference (WebSci10)Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge20102010 myown ol ontology semantics websci websci10 Thu Jun 17 20:34:50 CEST 2010Raleigh, NC, USAProceedings of the 19th International World Wide Web Conference (WWW 2010)aprStop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity20102010 collaborative myown tagging taggingsurvey www www2010 Recent research provides evidence for the presence of emergent semantics in collaborative tagging systems. While several methods have been proposed, little is known about the factors that influence the evolution of semantic structures in these systems. A natural hypothesis is that the quality of the emergent semantics depends on the pragmatics of tagging: Users with certain usage patterns might contribute more to the resulting semantics than others. In this work, we propose several measures which enable a pragmatic differentiation of taggers by their degree of contribution to emerging semantic structures. We distinguish between categorizers, who typically use a small set of tags as a replacement for hierarchical classification schemes, and describers, who are annotating resources with a wealth of freely associated, descriptive keywords. To study our hypothesis, we apply semantic similarity measures to 64 different partitions of a real-world and large-scale folksonomy containing different ratios of categorizers and describers. Our results not only show that ‘verbose’ taggers are most useful for the emergence of tag semantics, but also that a subset containing only 40% of the most ‘verbose’ taggers can produce results that match and even outperform the semantic precision obtained from the whole dataset. Moreover, the results suggest that there exists a causal link between the pragmatics of tagging and resulting emergent semantics. This work is relevant for designers and analysts of tagging systems interested (i) in fostering the semantic development of their platforms, (ii) in identifying users introducing “semantic noise”, and (iii) in learning ontologies.Thu Jun 17 20:34:10 CEST 2010Toronto, CanadaProceedings of the 21st ACM conference on Hypertext and hypermediaVisit me, click me, be my friend: An analysis of evidence networks of user relationships in Bibsonomy20102010 analysis evidence links myown networks sna social Thu Jun 10 09:13:43 CEST 2010Datenbank-Spektrum#jun#115--24Query Logs as Folksonomies1020102010 folksonomies logs myown query Query logs provide a valuable resource for preference information in search. A user clicking on a specific resource after submitting a query indicates that the resource has some relevance with respect to the query. To leverage the information ofquery logs, one can relate submitted queries from specific users to their clicked resources and build a tripartite graph ofusers, resources and queries. This graph resembles the folksonomy structure of social bookmarking systems, where users addtags to resources. In this article, we summarize our work on building folksonomies from query log files. The focus is on threecomparative studies of the system’s content, structure and semantics. Our results show that query logs incorporate typicalfolksonomy properties and that approaches to leverage the inherent semantics of folksonomies can be applied to query logsas well.