@inproceedings{wetzker2010translating, abstract = {Collaborative tagging services (folksonomies) have been among the stars of the Web 2.0 era. They allow their users to label diverse resources with freely chosen keywords (tags). Our studies of two real-world folksonomies unveil that individual users develop highly personalized vocabularies of tags. While these meet individual needs and preferences, the considerable differences between personal tag vocabularies (personomies) impede services such as social search or customized tag recommendation. In this paper, we introduce a novel user-centric tag model that allows us to derive mappings between personal tag vocabularies and the corresponding folksonomies. Using these mappings, we can infer the meaning of user-assigned tags and can predict choices of tags a user may want to assign to new items. Furthermore, our translational approach helps in reducing common problems related to tag ambiguity, synonymous tags, or multilingualism. We evaluate the applicability of our method in tag recommendation and tag-based social search. Extensive experiments show that our translational model improves the prediction accuracy in both scenarios.}, acmid = {1718497}, address = {New York, NY, USA}, author = {Wetzker, Robert and Zimmermann, Carsten and Bauckhage, Christian and Albayrak, Sahin}, booktitle = {Proceedings of the third ACM international conference on Web search and data mining}, doi = {10.1145/1718487.1718497}, interhash = {12e89c88182a393dae8d63287f65540d}, intrahash = {224e7bdc753e1823fc17828f2c760b6e}, isbn = {978-1-60558-889-6}, location = {New York, New York, USA}, numpages = {10}, pages = {71--80}, publisher = {ACM}, series = {WSDM '10}, title = {I tag, you tag: translating tags for advanced user models}, url = {http://doi.acm.org/10.1145/1718487.1718497}, year = 2010 } @article{burke2011recommendation, abstract = {Recommender systems are a means of personalizing the presentation of information to ensure that users see the items most relevant to them. The social web has added new dimensions to the way people interact on the Internet, placing the emphasis on user-generated content. Users in social networks create photos, videos and other artifacts, collaborate with other users, socialize with their friends and share their opinions online. This outpouring of material has brought increased attention to recommender systems, as a means of managing this vast universe of content. At the same time, the diversity and complexity of the data has meant new challenges for researchers in recommendation. This article describes the nature of recommendation research in social web applications and provides some illustrative examples of current research directions and techniques. It is difficult to overstate the impact of the social web. This new breed of social applications is reshaping nearly every human activity from the way people watch movies to how they overthrow governments. Facebook allows its members to maintain friendships whether they live next door or on another continent. With Twitter, users from celebrities to ordinary folks can launch their 140 character messages out to a diverse horde of ‘‘followers.” Flickr and YouTube users upload their personal media to share with the world, while Wikipedia editors collaborate on the world’s largest encyclopedia.}, author = {Burke, Robin and Gemmell, Jonathan and Hotho, Andreas and Jäschke, Robert}, interhash = {3089ca25de28ef0bc80bcdebd375a6f9}, intrahash = {41dbb2c9f71440c9aa402f8966117979}, journal = {AI Magazine}, number = 3, pages = {46--56}, publisher = {Association for the Advancement of Artificial Intelligence}, title = {Recommendation in the Social Web}, url = {http://www.aaai.org/ojs/index.php/aimagazine/article/view/2373}, volume = 32, year = 2011 } @phdthesis{jschke2011formal, address = {[Amsterdam]}, author = {Jäschke, Robert}, interhash = {dcb2cd1cd72ae45d77c4d8755d199405}, intrahash = {1ac91a922a872523de0ce8d4984e53a3}, isbn = {9781607507079 1607507072 9783898383325 3898383326}, pages = {--}, publisher = {IOS Press}, refid = {707172013}, title = {Formal concept analysis and tag recommendations in collaborative tagging systems}, url = {http://www.worldcat.org/search?qt=worldcat_org_all&q=9783898383325}, year = 2011 } @phdthesis{bogers2009recommender, abstract = {Recommender systems belong to a class of personalized information filtering technologies that aim to identify which items in a collection might be of interest to a particular user. Recommendations can be made using a variety of information sources related to both the user and the items: past user preferences, demographic information, item popularity, the metadata characteristics of the products, etc. Social bookmarking websites, with their emphasis on open collaborative information access, offer an ideal scenario for the application of recommender systems technology. They allow users to manage their favorite bookmarks online through a web interface and, in many cases, allow their users to tag the content they have added to the system with keywords. The underlying application then makes all information sharable among users. Examples of social bookmarking services include Delicious, Diigo, Furl, CiteULike, and BibSonomy. In my Ph.D. thesis I describe the work I have done on item recommendation for social bookmarking, i.e., recommending interesting bookmarks to users based on the content they bookmarked in the past. In my experiments I distinguish between two types of information sources. The first one is usage data contained in the folksonomy, which represents the past selections and transactions of all users, i.e., who added which items, and with what tags. The second information source is the metadata describing the bookmarks or articles on a social bookmarking website, such as title, description, authorship, tags, and temporal and publication-related metadata. I compare and combine the content-based aspect with the more common usage-based approaches. I evaluate my approaches on four data sets constructed from three different social bookmarking websites: BibSonomy, CiteULike, and Delicious. In addition, I investigate different combination methods for combining different algorithms and show which of those methods can successfully improve recommendation performance. Finally, I consider two growing pains that accompany the maturation of social bookmarking websites: spam and duplicate content. I examine how widespread each of these problems are for social bookmarking and how to develop effective automatic methods for detecting such unwanted content. Finally, I investigate the influence spam and duplicate content can have on item recommendation. }, address = {Tilburg, The Netherlands}, author = {Bogers, Toine}, interhash = {65b74dcabaa583a48469f3dec2ec1f62}, intrahash = {b02daac1201473600b7c8d2553865b4a}, month = dec, school = {Tilburg University}, title = {Recommender Systems for Social Bookmarking}, url = {http://ilk.uvt.nl/~toine/phd-thesis/}, year = 2009 } @inproceedings{rezel2010swefe, abstract = {This paper presents SWE-FE: a suite of methods to extend folksonomies to the worldwide Sensor Web in order to tackle the emergent data rich information poor (DRIP) syndrome afflicting most geospatial applications on the Internet. SWE-FE leverages the geospatial information associated with three key components of such collaborative tagging systems: tags, resources and users. Specifically, SWE-FE provides algorithms for: i) suggesting tags for users during the tag input stage; ii) generating tag maps which provides for serendipitous browsing; and iii) personalized searching within the folksonomy. We implement SWE-FE on the GeoCENS Sensor Web platform as a case study for assessing the efficacy of our methods. We outline the evaluation framework that we are currently employing to carry out this assessment.}, author = {Rezel, R. and Liang, S.}, booktitle = {2010 International Symposium on Collaborative Technologies and Systems (CTS)}, doi = {10.1109/CTS.2010.5478494}, interhash = {9eb696593932c517873232386f8f61bf}, intrahash = {d5b71572c7fea6504a0c0a3d84a9ecf0}, month = may, pages = {349--356}, publisher = {IEEE}, title = {SWE-FE: Extending folksonomies to the Sensor Web}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5478494}, year = 2010 } @article{Kammergruber2010a, abstract = {Digitally supported knowledge work, using tags for content organization, creates inherent challenges. In this paper we show the design of a corporate tagging framework facing these challenges. We describe the implementation of a thesaurus approach as a lightweight alternative to a more sophisticated ontology design. An RDF based architecture with a Web 2.0 style editor enables average users to enrich social tagging data with semantic relations. }, author = {Kammergruber, Walter Christian and Ehms, Karsten}, interhash = {d9907846571f0057629f0202bb4beb7d}, intrahash = {37048201a69ba88c0d56dcbf8d7f758b}, journal = {10th International Conference on Knowledge Management (I-KNOW '10)}, owner = {woidda}, pages = {11-18}, title = {A Corporate Tagging Framework as Integration Service for Knowledge Workers}, volume = 10, year = 2010 } @inproceedings{Kim2008, address = {Berlin, Deutschland}, author = {Kim, Hak Lae and Scerri, Simon and Breslin, John G. and Decker, Stefan and Kim, Hong Gee}, booktitle = {{Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications}}, interhash = {9c5f5af6f47a1a563dbb405c5a58a3cc}, intrahash = {7d3c3c2189394a8686ca9812d58bfe74}, pages = {128--137}, publisher = {{Dublin Core Metadata Initiative}}, title = {{The State of the Art in Tag Ontologies: A Semantic Model for Tagging and Folksonomies}}, year = 2008 } @article{10.1109/CSE.2009.75, address = {Los Alamitos, CA, USA}, author = {Zhou, Tom Chao and Ma, Hao and King, Irwin and Lyu, Michael R.}, doi = {10.1109/CSE.2009.75}, interhash = {010aefb7b22a666044909f4cea151963}, intrahash = {2b9dd91a3162d821abbe620942772464}, isbn = {978-0-7695-3823-5}, journal = {Computational Science and Engineering, IEEE International Conference on}, pages = {194-199}, publisher = {IEEE Computer Society}, title = {TagRec: Leveraging Tagging Wisdom for Recommendation}, url = {http://www.computer.org/portal/web/csdl/doi/10.1109/CSE.2009.75}, volume = 4, year = 2009 } @inproceedings{Cai:2011:LTD:1935826.1935920, abstract = {Social tagging recommendation is an urgent and useful enabling technology for Web 2.0. In this paper, we present a systematic study of low-order tensor decomposition approach that are specifically targeted at the very sparse data problem in tagging recommendation problem. Low-order polynomials have low functional complexity, are uniquely capable of enhancing statistics and also avoids over-fitting than traditional tensor decompositions such as Tucker and Parafac decompositions. We perform extensive experiments on several datasets and compared with 6 existing methods. Experimental results demonstrate that our approach outperforms existing approaches.}, acmid = {1935920}, address = {New York, NY, USA}, author = {Cai, Yuanzhe and Zhang, Miao and Luo, Dijun and Ding, Chris and Chakravarthy, Sharma}, booktitle = {Proceedings of the fourth ACM international conference on Web search and data mining}, doi = {10.1145/1935826.1935920}, interhash = {414f80ad09d994af6f448446c04cd226}, intrahash = {52a9e5fd121bf7be4fa8670cc93a7197}, isbn = {978-1-4503-0493-1}, location = {Hong Kong, China}, numpages = {10}, pages = {695--704}, publisher = {ACM}, series = {WSDM '11}, title = {Low-order tensor decompositions for social tagging recommendation}, url = {http://doi.acm.org/10.1145/1935826.1935920}, year = 2011 } @inproceedings{cattuto2008semantic, abstract = {Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For tasks like synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Eventhough most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptionson the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity interms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures oftag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding isprovided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measuresof semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of theinvestigated similarity measures and indicates which ones are better suited in the context of a given semantic application.}, author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd}, booktitle = {The Semantic Web - ISWC 2008}, doi = {10.1007/978-3-540-88564-1_39}, interhash = {b44538648cfd476d6c94e30bc6626c86}, intrahash = {4752f261d03cead0c52565148a0ba1c9}, isbn = {978-3-540-88563-4}, pages = {615--631}, publisher = {Springer Berlin / Heidelberg}, series = {Lecture Notes in Computer Science}, title = {Semantic Grounding of Tag Relatedness in Social Bookmarking Systems}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/cattuto2008semantica.pdf}, volume = 5318, year = 2008 } @article{citeulike:8506476, abstract = {{Social tagging systems pose new challenges to developers of recommender systems. As observed by recent research, traditional implementations of classic recommender approaches, such as collaborative filtering, are not working well in this new context. To address these challenges, a number of research groups worldwide work on adapting these approaches to the specific nature of social tagging systems. In joining this stream of research, we have developed and evaluated two enhancements of user-based collaborative filtering algorithms to provide recommendations of articles on Cite ULike, a social tagging service for scientific articles. The result obtained after two phases of evaluation suggests that both enhancements are beneficial. Incorporating the number of raters into the algorithms, as we do in our NwCF approach, leads to an improvement of precision, while tag-based BM25 similarity measure, an alternative to Pearson correlation for calculating the similarity between users and their neighbors, increases the coverage of the recommendation process.}}, address = {Los Alamitos, CA, USA}, author = {Santander, Denis P. and Brusilovsky, Peter}, citeulike-article-id = {8506476}, citeulike-linkout-0 = {http://doi.ieeecomputersociety.org/10.1109/WI-IAT.2010.261}, citeulike-linkout-1 = {http://dx.doi.org/10.1109/WI-IAT.2010.261}, doi = {10.1109/WI-IAT.2010.261}, interhash = {dd320da969151c01cf270976c0803274}, intrahash = {2c8764f2fe11ef1ae43fc0a5b51301ae}, isbn = {978-0-7695-4191-4}, journal = {Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on}, pages = {136--142}, posted-at = {2011-01-05 00:19:36}, priority = {0}, publisher = {IEEE Computer Society}, title = {{Improving Collaborative Filtering in Social Tagging Systems for the Recommendation of Scientific Articles}}, url = {http://dx.doi.org/10.1109/WI-IAT.2010.261}, volume = 1, year = 2010 } @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}, doi = {10.1007/s00778-010-0208-4}, interhash = {57fe43734b18909a24bf5bf6608d2a09}, intrahash = {c9437d5ec56ba949f533aeec00f571e3}, issn = {1066-8888}, journal = {The VLDB Journal}, 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 } @article{hotho2010publikationsmanagement, abstract = {Kooperative Verschlagwortungs- bzw. Social-Bookmarking-Systeme wie Delicious, Mister Wong oder auch unser eigenes System BibSonomy erfreuen sich immer gr{\"o}{\ss}erer Beliebtheit und bilden einen zentralen Bestandteil des heutigen Web 2.0. In solchen Systemen erstellen Nutzer leichtgewichtige Begriffssysteme, sogenannte Folksonomies, die die Nutzerdaten strukturieren. Die einfache Bedienbarkeit, die Allgegenw{\"a}rtigkeit, die st{\"a}ndige Verf{\"u}gbarkeit, aber auch die M{\"o}glichkeit, Gleichgesinnte spontan in solchen Systemen zu entdecken oder sie schlicht als Informationsquelle zu nutzen, sind Gr{\"u}nde f{\"u}r ihren gegenw{\"a}rtigen Erfolg. Der Artikel f{\"u}hrt den Begriff Social Bookmarking ein und diskutiert zentrale Elemente (wie Browsing und Suche) am Beispiel von BibSonomy anhand typischer Arbeitsabl{\"a}ufe eines Wissenschaftlers. Wir beschreiben die Architektur von BibSonomy sowie Wege der Integration und Vernetzung von BibSonomy mit Content-Management-Systemen und Webauftritten. Der Artikel schlie{\ss}t mit Querbez{\"u}gen zu aktuellen Forschungsfragen im Bereich Social Bookmarking.}, author = {Hotho, Andreas and Benz, Dominik and Eisterlehner, Folke and J{\"a}schke, Robert and Krause, Beate and Schmitz, Christoph and Stumme, Gerd}, file = {dpunkt Product page:http\://hmd.dpunkt.de/271/05.html:URL}, interhash = {4555775b639fe1ec65a302a61ee6532c}, intrahash = {250d83c41fb10b89c73f54bd7040bd6e}, issn = {1436-3011}, journal = {HMD -- Praxis der Wirtschaftsinformatik}, month = {#feb#}, pages = {47-58}, title = {{Publikationsmanagement mit BibSonomy -- ein Social-Bookmarking-System f{\"u}r Wissenschaftler}}, volume = {Heft 271}, year = 2010 } @incollection{reference/rsh/MarinhoNSJHSS11, author = {Marinho, Leandro Balby and Nanopoulos, Alexandros and Schmidt-Thieme, Lars and Jäschke, Robert and Hotho, Andreas and Stumme, Gerd and Symeonidis, Panagiotis}, booktitle = {Recommender Systems Handbook}, crossref = {reference/rsh/2011}, editor = {Ricci, Francesco and Rokach, Lior and Shapira, Bracha and Kantor, Paul B.}, ee = {http://dx.doi.org/10.1007/978-0-387-85820-3_19}, interhash = {2d4afa6f7fb103ccc166c9c5d629cdd1}, intrahash = {8a520671b6ced7c4b81b1cd18274e0ee}, isbn = {978-0-387-85819-7}, pages = {615-644}, publisher = {Springer}, title = {Social Tagging Recommender Systems.}, url = {http://dblp.uni-trier.de/db/reference/rsh/rsh2011.html#MarinhoNSJHSS11}, year = 2011 } @inproceedings{conf/wsdm/HeymannPG10, author = {Heymann, Paul and Paepcke, Andreas and Garcia-Molina, Hector}, booktitle = {WSDM}, crossref = {conf/wsdm/2010}, editor = {Davison, Brian D. and Suel, Torsten and Craswell, Nick and Liu, Bing}, ee = {http://doi.acm.org/10.1145/1718487.1718495}, interhash = {d4f72ed57e6b99dbe32e18e218d81ef5}, intrahash = {12579231cd5449f9a40cba9924975f09}, isbn = {978-1-60558-889-6}, pages = {51-60}, publisher = {ACM}, title = {Tagging human knowledge.}, url = {http://dblp.uni-trier.de/db/conf/wsdm/wsdm2010.html#HeymannPG10}, year = 2010 } @article{springerlink:10.1007/s00287-010-0485-8, abstract = {Soziale Tagging-Systeme gehören zu den in den vergangenen Jahren entstandenen Web2.0-Systemen. Sie ermöglichen es Anwendern, beliebige Informationen in das Internet einzustellen und untereinander auszutauschen. Je nach Anbieter verlinken Nutzer Videos, Fotos oder Webseiten und beschreiben die eingestellten Medien mit entsprechenden Schlagwörtern (Tags). Die damit einhergehende freiwillige Preisgabe oftmals persönlicher Informationen wirft Fragen im Bereich der informationellen Selbstbestimmung auf. Dieses Grundrecht gewährleistet dem Einzelnen, grundsätzlich selbst über die Preisgabe und Verwendung seiner persönlichen Daten zu bestimmen. Für viele Funktionalitäten, wie beispielsweise Empfehlungsdienste oder die Bereitstellung einer API, ist eine solche Kontrolle allerdings schwierig zu gestalten. Oftmals existieren keine Richtlinien, inwieweit Dienstanbieter und weitere Dritte diese öffentlichen Daten (und weitere Daten, die bei der Nutzung des Systems anfallen) nutzen dürfen. Dieser Artikel diskutiert anhand eines konkreten Systems typische, für den Datenschutz relevante Funktionalitäten und gibt Handlungsanweisungen für eine datenschutzkonforme technische Gestaltung.}, address = {Berlin / Heidelberg}, affiliation = {Fachgebiet Wissensverarbeitung, Universität Kassel, Kassel, Deutschland}, author = {Krause, Beate and Lerch, Hana and Hotho, Andreas and Roßnagel, Alexander and Stumme, Gerd}, doi = {10.1007/s00287-010-0485-8}, interhash = {dc30e162dbb8700abdde78f86037cf2e}, intrahash = {69f3738deecd73594907183aa874ec1a}, issn = {0170-6012}, journal = {Informatik-Spektrum}, keyword = {Computer Science}, pages = {1-12}, publisher = {Springer}, title = {Datenschutz im Web 2.0 am Beispiel des sozialen Tagging-Systems BibSonomy}, url = {http://dx.doi.org/10.1007/s00287-010-0485-8}, year = 2010 } @inproceedings{koerner2010thinking, abstract = {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.}, address = {Raleigh, NC, USA}, author = {Körner, Christian and Benz, Dominik and Strohmaier, Markus and Hotho, Andreas and Stumme, Gerd}, booktitle = {Proceedings of the 19th International World Wide Web Conference (WWW 2010)}, interhash = {5afe6e4ce8357d8ac9698060fb438468}, intrahash = {45f8d8f2a8251a5e988c596a5ebb3f2d}, month = apr, publisher = {ACM}, title = {Stop Thinking, start Tagging - Tag Semantics emerge from Collaborative Verbosity}, url = {http://www.kde.cs.uni-kassel.de/benz/papers/2010/koerner2010thinking.pdf}, year = 2010 } @inproceedings{Angeletou08semanticallyenriching, abstract = {Abstract. While the increasing popularity of folksonomies has lead to a vast quantity of tagged data, resource retrieval in folksonomies is limited by being agnostic to the meaning (i.e., semantics) of tags. Our goal is to automatically enrich folksonomy tags (and implicitly the related resources) with formal semantics by associating them to relevant concepts defined in online ontologies. We introduce FLOR, a method that performs automatic folksonomy enrichment by combining knowledge from WordNet and online available ontologies. Experimentally testing FLOR, we found that it correctly enriched 72 % of 250 Flickr photos. 1}, author = {Angeletou, Sofia and Sabou, Marta and Motta, Enrico}, booktitle = {In Proc of the 5th ESWC. workshop: Collective Intelligence & the Semantic Web}, interhash = {1b244d0220730e994822192f6e1cba76}, intrahash = {cd78f2e97127932ea36b7014c3d15aa6}, title = {Semantically enriching folksonomies with FLOR}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.2569}, year = 2008 } @inproceedings{Van-Damme2007, address = {Innsbruck}, author = {Damme, C{\'e}line Van and Hepp, Martin and Siorpaes, Katharina}, bdsk-file-1 = {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}, bdsk-url-1 = {http://www.kde.cs.uni-kassel.de/ws/eswc2007/proc/ProceedingsSemnet07.pdf}, booktitle = {Bridging the Gap between Semantic Web and Web 2.0 (SemNet 2007)}, date-added = {2009-08-17 11:40:57 +0200}, date-modified = {2010-01-04 09:30:08 +0100}, interhash = {c8d1bcaa606229417f1c3f0f27c5f0e0}, intrahash = {8d57c1e57c7aba60acb767e3d5b0fa13}, pages = {57--70}, title = {FolksOntology: An Integrated Approach for Turning Folksonomies into Ontologies}, url = {http://www.kde.cs.uni-kassel.de/ws/eswc2007/proc/ProceedingsSemnet07.pdf}, urldate = {28.5.2008}, year = 2007 } @inproceedings{Zhou/2007/Unsupervised, abstract = {This paper deals with the problem of exploring hierarchical semantics from social annotations. Recently, social annotation services have become more and more popular in Semantic Web. It allows users to arbitrarily annotate web resources, thus, largely lowers the barrier to cooperation. Furthermore, through providing abundant meta-data resources, social annotation might become a key to the development of Semantic Web. However, on the other hand, social annotation has its own apparent limitations, for instance, 1) ambiguity and synonym phenomena and 2) lack of hierarchical information. In this paper, we propose an unsupervised model to automatically derive hierarchical semantics from social annotations. Using a social bookmark service Del.icio.us as example, we demonstrate that the derived hierarchical semantics has the ability to compensate those shortcomings. We further apply our model on another data set from Flickr to testify our model's applicability on different environments. The experimental results demonstrate our model's effciency.}, address = {Berlin, Heidelberg}, author = {Zhou, Mianwei and Bao, Shenghua and Wu, Xian and Yu, Yong}, booktitle = {Proceedings of the 6th International Semantic Web Conference and 2nd Asian Semantic Web Conference (ISWC/ASWC2007), Busan, South Korea}, crossref = {http://data.semanticweb.org/conference/iswc-aswc/2007/proceedings}, editor = {Aberer, Karl and Choi, Key-Sun and Noy, Natasha and Allemang, Dean and Lee, Kyung-Il and Nixon, Lyndon J B and Golbeck, Jennifer and Mika, Peter and Maynard, Diana and Schreiber, Guus and Cudré-Mauroux, Philippe}, interhash = {af21595ee9f4a13b5e651ad049f31262}, intrahash = {355fcbb32255f3ba5f41819c00c520ba}, month = {November}, pages = {673--686}, publisher = {Springer Verlag}, series = {LNCS}, title = {An Unsupervised Model for Exploring Hierarchical Semantics from Social Annotations}, url = {http://iswc2007.semanticweb.org/papers/673.pdf}, volume = 4825, year = 2007 }