@misc{citeulike:484851, title = {Collaborative tagging as a tripartite network}, author = {R. Lambiotte and M. Ausloos}, month = {Dec}, note = {{\tt arXiv:cs.DS/0512090}}, year = 2005, url = {http://arxiv.org/abs/cs.DS/0512090}, id = {484851}, priority = {3}, comment = {Paper about the three parts USERS, RESOURCES and TAGS.}, eprint = {cs.DS/0512090}, abstract = {We describe online collaborative communities by tripartite networks, the nodes being persons, items and tags. We introduce projection methods in order to uncover the structures of the networks, i.e. communities of users, genre families...
To do so, we focus on the correlations between the nodes, depending on their profiles, and use percolation techniques that consist in removing less correlated links and observing the shaping of disconnected islands. The structuring of the network is visualised by using a tree representation. The notion of diversity in the system is also discussed.}, biburl = {http://www.bibsonomy.org/bibtex/265c6f348a54f872fb3e60b4bd64b485b/stumme}, keywords = {FCA OntologyHandbook collaboration discovery folksonomy tagging taxonomy} } @inproceedings{jaeschke06trias, title = {TRIAS - An Algorithm for Mining Iceberg Tri-Lattices}, address = {Hong Kong}, author = {Robert J�schke and Andreas Hotho and Christoph Schmitz and Bernhard Ganter and Gerd Stumme}, booktitle = {Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06)}, month = {December}, pages = {907-911}, publisher = {IEEE Computer Society}, year = 2006, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/jaeschke2006trias.pdf}, issn = {1550-4786}, isbn = {0-7695-2701-9}, vgwort = {19}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.162}, biburl = {http://www.bibsonomy.org/bibtex/238ab0f59191ec7ed1f0e9325685c2860/stumme}, keywords = {2006 FCA OntologyHandbook algorithm analysis concept fca folksonomies folksonomy formal iceberg lattices myown nepomuk tagging tri triadic trias} } @techreport{GH05structure, title = {The Structure of Collaborative Tagging Systems}, author = {Scott Golder and Bernardo A. Huberman}, institution = {Information Dynamics Lab, HP Labs }, month = {Aug}, year = 2005, url = {http://arxiv.org/abs/cs.DL/0508082}, id = {305755}, priority = {2}, eprint = {cs.DL/0508082}, biburl = {http://www.bibsonomy.org/bibtex/250f762bd270eeda14f71474e3c38795b/stumme}, keywords = {FCA OntologyHandbook folksonomy structure tagging} } @inproceedings{dkmnrt06visualizing, title = {Visualizing Tags over Time}, author = {M. Dubinko and R. Kumar and J. Magnani and J. Novak and P. Raghavan and A. Tomkins}, booktitle = {Proc. of the 15th International WWW Conference}, year = 2006, day = {23-25}, biburl = {http://www.bibsonomy.org/bibtex/2e14f92577c8819bfd9753a047c6a8cea/stumme}, keywords = {FCA OntologyHandbook tagging time visualizing} } @misc{Cattuto2006, title = {Collaborative Tagging and Semiotic Dynamics}, author = {Ciro Cattuto and Vittorio Loreto and Luciano Pietronero}, month = {May}, note = {{\tt arXiv:cs.CY/0605015}}, year = 2006, url = {http://arxiv.org/abs/cs/0605015}, id = {695889}, priority = {3}, eprint = {cs/0605015}, abstract = {Collaborative tagging has been quickly gaining ground because of its ability to recruit the activity of web users into effectively organizing and sharing vast amounts of information. Here we collect data from a popular system and investigate the statistical properties of tag co-occurrence. We introduce a stochastic model of user behavior embodying two main aspects of collaborative tagging: (i) a frequency-bias mechanism related to the idea that users are exposed to each other's tagging activity; (ii) a notion of memory - or aging of resources - in the form of a heavy-tailed access to the past state of the system. Remarkably, our simple modeling is able to account quantitatively for the observed experimental features, with a surprisingly high accuracy. This points in the direction of a universal behavior of users, who - despite the complexity of their own cognitive processes and the uncoordinated and selfish nature of their tagging activity - appear to follow simple activity patterns.}, biburl = {http://www.bibsonomy.org/bibtex/28d265ea13915a79ec08fe13b8e7074c7/stumme}, keywords = {FCA OntologyHandbook folksonomy research tagging taxonomy} } @inproceedings{1180904, title = {tagging, communities, vocabulary, evolution}, address = {New York, NY, USA}, author = {Shilad Sen and Shyong K. Lam and Al Mamunur Rashid and Dan Cosley and Dan Frankowski and Jeremy Osterhouse and F. Maxwell Harper and John Riedl}, booktitle = {CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work}, pages = {181--190}, publisher = {ACM}, year = 2006, url = {http://portal.acm.org/citation.cfm?id=1180904}, location = {Banff, Alberta, Canada}, isbn = {1-59593-249-6}, doi = {http://doi.acm.org/10.1145/1180875.1180904}, description = {tagging, communities, vocabulary, evolution}, abstract = {A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.}, biburl = {http://www.bibsonomy.org/bibtex/2582641c05e7a0b9396945a951822c83f/stumme}, keywords = {communities community evolution folksonomies folksonomy tagging vocabulary} } @inproceedings{grahl2007clustering, title = {Conceptual Clustering of Social Bookmarking Sites}, address = {Graz, Austria}, author = {Miranda Grahl and Andreas Hotho and Gerd Stumme}, booktitle = {7th International Conference on Knowledge Management (I-KNOW '07)}, month = {SEP}, pages = {356-364}, publisher = {Know-Center}, year = 2007, issn = {0948-695x}, abstract = {Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of the system, but it does not allow a conceptual drill-down, e. g., along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented with ranked lists of users and resources most related to each cluster. The rankings are computed using our FolkRank algorithm. We have evaluated our approach on large scale data from the del.icio.us bookmarking system.}, biburl = {http://www.bibsonomy.org/bibtex/2334d3ab11400c4a3ea3ed5b1e95c1855/stumme}, keywords = {2007 folksonomies folksonomy myown sites social tagging} } @misc{santosneto07, title = {Tracking User Attention in Collaborative Tagging Communities}, author = {Elizeu Santos-Neto and Matei Ripeanu and Adriana Iamnitchi}, year = 2007, url = {http://arxiv.org/pdf/0705.1013}, description = {[0705.1013] Tracking User Attention in Collaborative Tagging Communities}, biburl = {http://www.bibsonomy.org/bibtex/2785df87d0942d1cb6da9b944df902730/stumme}, keywords = {Communities Tagging User bibsonomy citeulike communities folksonomy tracking user} } @inproceedings{magnani_visualtags_2006, title = {Visualizing tags over time}, address = {New York, NY, USA}, author = {Micah Dubinko and Ravi Kumar and Joseph Magnani and Jasmine Novak and Prabhakar Raghavan and Andrew Tomkins}, booktitle = {WWW '06: Proceedings of the 15th international conference on World Wide Web}, pages = {193--202}, publisher = {ACM Press}, year = 2006, url = {http://portal.acm.org/citation.cfm?id=1135810}, location = {Edinburgh, Scotland}, isbn = {1-59593-323-9}, doi = {http://doi.acm.org/10.1145/1135777.1135810}, description = {Visualizing tags over time}, abstract = {We consider the problem of visualizing the evolution of tags within the Flickr (flickr.com) online image sharing community. Any user of the Flickr service may append a tag to any photo in the system. Over the past year, users have on average added over a million tags each week. Understanding the evolution of these tags over time is therefore a challenging task. We present a new approach based on a characterization of the most interesting tags associated with a sliding interval of time. An animation provided via Flash in a web browser allows the user to observe and interact with the interesting tags as they evolve over time.New algorithms and data structures are required to support the efficient generation of this visualization. We combine a novel solution to an interval covering problem with extensions to previous work on score aggregation in order to create an efficient backend system capable of producing visualizations at arbitrary scales on this large dataset in real time.}, biburl = {http://www.bibsonomy.org/bibtex/2cca8a679a78e2bced9a5cc268cfd3aaa/stumme}, keywords = {folksonomies tagging visualisation visualizing} } @inproceedings{conf/ijcai/HayesAV07, title = {An Analysis of the Use of Tags in a Blog Recommender System.}, author = {Conor Hayes and Paolo Avesani and Sriharsha Veeramachaneni}, booktitle = {IJCAI}, crossref = {conf/ijcai/2007}, editor = {Manuela M. Veloso}, pages = {2772-2777}, year = 2007, url = {www.ijcai.org/papers07/Papers/IJCAI07-445.pdf }, ee = {http://www.ijcai.org/papers07/Papers/IJCAI07-445.pdf}, date = {2007-03-05}, biburl = {http://www.bibsonomy.org/bibtex/207ee256c7cd4433fc0bde4002c7bc90c/stumme}, keywords = {analysis blog folksonomy recommender tagging} }